search

SwissDataScienceCenter / mlschema-model-converters

Apache License 2.0
3 stars 0 forks source link

mls from autosklearn #5

Open chrisbarber opened 4 years ago

chrisbarber commented 4 years ago

took this example from autosklearn and passed it to to_mls and it produces something

{
  "identifier":"01c6d5de-441d-48d4-a1d6-5df373d73191",
  "executes":{
    "_id":"_:autosklearn.estimators.AutoSklearnRegressor",
    "identifier":"78a70bb4-0851-4ae2-94a8-d80c93b654e7",
    "name":null,
    "parameters":[
      {
        "_id":"_:delete_output_folder_after_terminate",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:delete_tmp_folder_after_terminate",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:disable_evaluator_output",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:ensemble_memory_limit",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:ensemble_nbest",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:ensemble_size",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:exclude_estimators",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:exclude_preprocessors",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:get_smac_object_callback",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:include_estimators",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:include_preprocessors",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:initial_configurations_via_metalearning",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:logging_config",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:max_models_on_disc",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:metadata_directory",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:ml_memory_limit",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:n_jobs",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:output_folder",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:per_run_time_limit",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:resampling_strategy",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:resampling_strategy_arguments",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:seed",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:shared_mode",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:smac_scenario_args",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:time_left_for_this_task",
        "@type":"mls:HyperParameter"
      },
      {
        "_id":"_:tmp_folder",
        "@type":"mls:HyperParameter"
      }
    ],
    "implements":{
      "_id":"_:autosklearn.estimators.AutoSklearnRegressor",
      "@type":"mls:Algorithm"
    },
    "version":null,
    "@type":"mls:Implementation"
  },
  "input_values":[
    {
      "value":true,
      "specified_by":{
        "@id":"_:delete_output_folder_after_terminate"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":true,
      "specified_by":{
        "@id":"_:delete_tmp_folder_after_terminate"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":false,
      "specified_by":{
        "@id":"_:disable_evaluator_output"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":1024,
      "specified_by":{
        "@id":"_:ensemble_memory_limit"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":50,
      "specified_by":{
        "@id":"_:ensemble_nbest"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":50,
      "specified_by":{
        "@id":"_:ensemble_size"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":25,
      "specified_by":{
        "@id":"_:initial_configurations_via_metalearning"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":50,
      "specified_by":{
        "@id":"_:max_models_on_disc"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":3072,
      "specified_by":{
        "@id":"_:ml_memory_limit"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":"/tmp/autosklearn_regression_example_out",
      "specified_by":{
        "@id":"_:output_folder"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":30,
      "specified_by":{
        "@id":"_:per_run_time_limit"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":"holdout",
      "specified_by":{
        "@id":"_:resampling_strategy"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":1,
      "specified_by":{
        "@id":"_:seed"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":false,
      "specified_by":{
        "@id":"_:shared_mode"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":120,
      "specified_by":{
        "@id":"_:time_left_for_this_task"
      },
      "@type":"mls:HyperParameterSetting"
    },
    {
      "value":"/tmp/autosklearn_regression_example_tmp",
      "specified_by":{
        "@id":"_:tmp_folder"
      },
      "@type":"mls:HyperParameterSetting"
    }
  ],
  "output_values":[

  ],
  "realizes":null,
  "version":null,
  "name":null,
  "@context":{
    "mls":"http://www.w3.org/ns/mls#",
    "@version":1.1,
    "_id":"@id",
    "dcterms":"http://purl.org/dc/terms/",
    "executes":{
      "@id":"mls:executes",
      "@context":{
        "mls":"http://www.w3.org/ns/mls#",
        "@version":1.1,
        "_id":"@id",
        "dcterms":"http://purl.org/dc/terms/",
        "name":"dcterms:title",
        "parameters":{
          "@id":"mls:hasHyperParameter",
          "@context":{
            "mls":"http://www.w3.org/ns/mls#",
            "@version":1.1,
            "_id":"@id"
          }
        },
        "implements":{
          "@id":"mls:implements",
          "@context":{
            "mls":"http://www.w3.org/ns/mls#",
            "@version":1.1,
            "_id":"@id"
          }
        },
        "version":"dcterms:hasVersion"
      }
    },
    "input_values":{
      "@id":"mls:hasInput",
      "@context":{
        "mls":"http://www.w3.org/ns/mls#",
        "@version":1.1,
        "_id":"@id",
        "xsd":"http://www.w3.org/2001/XMLSchema#",
        "specified_by":"mls:specifiedBy",
        "value":"mls:hasValue"
      }
    },
    "output_values":{
      "@id":"mls:hasOutput",
      "@context":{
        "mls":"http://www.w3.org/ns/mls#",
        "@version":1.1,
        "_id":"@id",
        "xsd":"http://www.w3.org/2001/XMLSchema#",
        "specified_by":"mls:specifiedBy",
        "value":"mls:hasValue"
      }
    },
    "realizes":{
      "@id":"mls:implements",
      "@context":{
        "mls":"http://www.w3.org/ns/mls#",
        "@version":1.1,
        "_id":"@id"
      }
    },
    "version":"dcterms:hasVersion",
    "name":"dcterms:title"
  },
  "@type":"mls:Run"
}

so i guess they support the get_params convention.

this is before calling fit on the model which segfaults on my mac for this case

vigsterkr commented 4 years ago

ah... yeah cool good that they 'fully' follow sklearn api, although i was hoping for that :) yeah actually after fit would be interesting.... i reckon we'll have to do some sort of special case for it as in GridCV to get all the details of various models that were fit etc

chrisbarber commented 4 years ago

don't know what's going on here.. tried this package on two OS's now, different versions of it, examples from the website and from the repo, different versions of swig, looking through bug reports... i am getting segfaults, runtime errors, scripts that just don't end after leaving them.. somebody has a docker image i guess but it's not official. what is the deal with this package? i mean.. i can dig in more but i'm just wondering how many people have a working set up of this and on what systems. i've tried on macos 10.15.4 and linux 5.6.0-1 (debian)

vigsterkr commented 4 years ago

https://hub.docker.com/r/mfeurer/auto-sklearn/ should work

chrisbarber commented 4 years ago

Okay, I fixed my issue.

Unfortunately auto-sklearn get_params returns the exact same thing, before and after fit and predict, at least for this example (regression). So the to_mls succeeds afterwards of course but I won't paste the output because it is identical to the above.

vigsterkr commented 4 years ago

yea but the question is what's the reference for the actual trained models.... after fit

vigsterkr commented 4 years ago

so like basically: https://github.com/automl/auto-sklearn/blob/master/autosklearn/estimators.py#L329 self._automl will have the reference for the trained machines.... and those should be iterated over and get_params()-ed and check the evaluation metrics result etc. and that should be exported into the jsonld

vigsterkr commented 4 years ago

any update on this?

chrisbarber commented 4 years ago

sorry been a bit irregular w/ splitting time w/ another project. i'll catch up at some point

chrisbarber commented 4 years ago

fyi i get:

>>> automl._automl[0].get_params()
Traceback (most recent call last):
  File "<console>", line 1, in <module>
  File "/Users/barberc/software/anaconda/envs/auto-sklearn/lib/python3.8/site-packages/sklearn/base.py", line 189, in get_params
    for key in self._get_param_names():
  File "/Users/barberc/software/anaconda/envs/auto-sklearn/lib/python3.8/site-packages/sklearn/base.py", line 164, in _get_param_names
    raise RuntimeError("scikit-learn estimators should always "
RuntimeError: scikit-learn estimators should always specify their parameters in the signature of their __init__ (no varargs). <class 'autosklearn.automl.AutoMLRegressor'> with constructor (self, *args, **kwargs) doesn't  follow this convention.

furthermore ._automl is a private attribute...

It seems like this functionality should live in auto-sklearn, and this weird pickiness of sklearn about subclass __init__ arguments should also be addressed there.

vigsterkr commented 4 years ago

furthermore ._automl is a private attribute...

in python that's all just convention.... right? nothing there to enforce of it's 'private-ness', see https://docs.python.org/3.7/tutorial/classes.html#tut-private

vigsterkr commented 4 years ago

and fyi:

automl.get_models_with_weights()[0][1].get_params()

and so forth and so on.... basically that contains how the pipeline looks like, each parts' parametrization is available as a value for config key, see:

{'config': Configuration:
   balancing:strategy, Value: 'none'
   classifier:__choice__, Value: 'random_forest'
   classifier:random_forest:bootstrap, Value: 'True'
   classifier:random_forest:criterion, Value: 'gini'
   classifier:random_forest:max_depth, Constant: 'None'
   classifier:random_forest:max_features, Value: 0.48772464140872207
   classifier:random_forest:max_leaf_nodes, Constant: 'None'
   classifier:random_forest:min_impurity_decrease, Constant: 0.0
   classifier:random_forest:min_samples_leaf, Value: 1
   classifier:random_forest:min_samples_split, Value: 16
   classifier:random_forest:min_weight_fraction_leaf, Constant: 0.0
   data_preprocessing:categorical_transformer:categorical_encoding:__choice__, Value: 'no_encoding'
   data_preprocessing:categorical_transformer:category_coalescence:__choice__, Value: 'minority_coalescer'
   data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction, Value: 0.010000000000000004
   data_preprocessing:numerical_transformer:imputation:strategy, Value: 'most_frequent'
   data_preprocessing:numerical_transformer:rescaling:__choice__, Value: 'normalize'
   feature_preprocessor:__choice__, Value: 'polynomial'
   feature_preprocessor:polynomial:degree, Value: 2
   feature_preprocessor:polynomial:include_bias, Value: 'False'
   feature_preprocessor:polynomial:interaction_only, Value: 'False',
 'dataset_properties': {'task': 1,
  'sparse': False,
  'multilabel': False,
  'multiclass': False,
  'target_type': 'classification',
  'signed': False},
 'exclude': {},
 'include': {},
 'init_params': {'instance': '{"task_id": "breast_cancer"}'},
 'random_state': <mtrand.RandomState at 0x7fea9bebc240>,
 'steps': [('data_preprocessing',
   DataPreprocessor(categorical_features=None, config=None,
                    dataset_properties=None, exclude=None,
                    force_sparse_output=None, include=None, init_params=None,
                    pipeline=None, random_state=None)),
  ('balancing', Balancing(random_state=None, strategy='none')),
  ('feature_preprocessor',
   <autosklearn.pipeline.components.feature_preprocessing.FeaturePreprocessorChoice at 0x7feaa097c198>),
  ['classifier',
   <autosklearn.pipeline.components.classification.ClassifierChoice at 0x7feaa097cc88>]],
 'data_preprocessing': DataPreprocessor(categorical_features=None, config=None,
                  dataset_properties=None, exclude=None,
                  force_sparse_output=None, include=None, init_params=None,
                  pipeline=None, random_state=None),
 'balancing': Balancing(random_state=None, strategy='none'),
 'feature_preprocessor': <autosklearn.pipeline.components.feature_preprocessing.FeaturePreprocessorChoice at 0x7feaa097c198>,
 'classifier': <autosklearn.pipeline.components.classification.ClassifierChoice at 0x7feaa097cc88>,
 'data_preprocessing__categorical_features': None,
 'data_preprocessing__config': None,
 'data_preprocessing__dataset_properties': None,
 'data_preprocessing__exclude': None,
 'data_preprocessing__force_sparse_output': None,
 'data_preprocessing__include': None,
 'data_preprocessing__init_params': None,
 'data_preprocessing__pipeline': None,
 'data_preprocessing__random_state': None,
 'balancing__random_state': None,
 'balancing__strategy': 'none'}

but of course you can extract the model's param directly as well:

automl.get_models_with_weights()[0][1].get_params()['classifier'].choice.get_params()
{'bootstrap': True,
 'class_weight': None,
 'criterion': 'gini',
 'max_depth': None,
 'max_features': 0.48772464140872207,
 'max_leaf_nodes': None,
 'min_impurity_decrease': 0.0,
 'min_samples_leaf': 1,
 'min_samples_split': 16,
 'min_weight_fraction_leaf': 0.0,
 'n_jobs': 1,
 'random_state': <mtrand.RandomState at 0x7feaa06c27e0>}
chrisbarber commented 4 years ago

Here is some json. Basically the same as the generic sklearn one but with this additional snippet: https://github.com/ratschlab/mlschema-model-converters/blob/75dae1addc7f7d5d17d7d349f2645e737789a3f4/mlsconverters/autosklearn.py#L51-L54 And some handling for various objects that it has in the output of get_params.

{
    "identifier": "2497ad25-83f6-410c-ad90-0f8b8d002f74",
    "executes": {
        "_id": "_:autosklearn.automl.AutoML",
        "identifier": "041d0a07-9972-4daa-b2f3-b88d60684399",
        "name": null,
        "parameters": [
            {
                "_id": "_:@value",
                "@type": "mls:HyperParameter"
            }
        ],
        "implements": {
            "_id": "_:autosklearn.automl.AutoML",
            "@type": "mls:Algorithm"
        },
        "version": null,
        "@type": "mls:Implementation"
    },
    "input_values": [
        {
            "value": {
                "type": "autosklearn.automl.AutoML",
                "params": {
                    "backend": null,
                    "debug_mode": null,
                    "disable_evaluator_output": null,
                    "ensemble_memory_limit": null,
                    "ensemble_nbest": null,
                    "ensemble_size": null,
                    "exclude_estimators": null,
                    "exclude_preprocessors": null,
                    "get_smac_object_callback": null,
                    "include_estimators": null,
                    "include_preprocessors": null,
                    "initial_configurations_via_metalearning": null,
                    "keep_models": null,
                    "logging_config": null,
                    "max_models_on_disc": null,
                    "metadata_directory": null,
                    "ml_memory_limit": null,
                    "per_run_time_limit": null,
                    "precision": 32,
                    "resampling_strategy": null,
                    "resampling_strategy_arguments": null,
                    "seed": null,
                    "shared_mode": null,
                    "smac_scenario_args": null,
                    "time_left_for_this_task": null
                }
            },
            "specified_by": {
                "@id": "_:@value"
            },
            "@type": "mls:HyperParameterSetting"
        }
    ],
    "output_values": [
        {
            "_id": null,
            "value": [
                1.0,
                {
                    "@value": {
                        "type": "autosklearn.pipeline.classification.SimpleClassificationPipeline",
                        "params": {
                            "config": {
                                "balancing:strategy": "none",
                                "classifier:__choice__": "random_forest",
                                "data_preprocessing:categorical_transformer:categorical_encoding:__choice__": "one_hot_encoding",
                                "data_preprocessing:categorical_transformer:category_coalescence:__choice__": "minority_coalescer",
                                "data_preprocessing:numerical_transformer:imputation:strategy": "mean",
                                "data_preprocessing:numerical_transformer:rescaling:__choice__": "standardize",
                                "feature_preprocessor:__choice__": "no_preprocessing",
                                "classifier:random_forest:bootstrap": "True",
                                "classifier:random_forest:criterion": "gini",
                                "classifier:random_forest:max_depth": "None",
                                "classifier:random_forest:max_features": 0.5,
                                "classifier:random_forest:max_leaf_nodes": "None",
                                "classifier:random_forest:min_impurity_decrease": 0.0,
                                "classifier:random_forest:min_samples_leaf": 1,
                                "classifier:random_forest:min_samples_split": 2,
                                "classifier:random_forest:min_weight_fraction_leaf": 0.0,
                                "data_preprocessing:categorical_transformer:category_coalescence:minority_coalescer:minimum_fraction": 0.01
                            },
                            "dataset_properties": {
                                "task": 2,
                                "sparse": false,
                                "multilabel": false,
                                "multiclass": true,
                                "target_type": "classification",
                                "signed": false
                            },
                            "exclude": {},
                            "include": {},
                            "init_params": {
                                "instance": "{\"task_id\": \"e5941b9de02ebe2c0457a6ec6eb35c17\"}"
                            },
                            "random_state": [
                                "MT19937",
                                [1, 1812433254, 3713160357, 3109174145, 64984499, 3392658084, 446538473, 2629760756, 2453345558, 1394803949, 1021787430, 2063496713, 1304877364, 1713639158, 889001601, 1651239412, 1450863289, 745575081, 361057727, 2288771950, 1463387568, 2249488362, 26637982, 204036717, 1655702041, 1329048465, 2092351466, 1681619666, 3220660315, 1301783610, 626286181, 294669048, 3537128440, 3259518248, 2550101273, 1160881866, 308703547, 295714668, 35508674, 1599247281, 376272024, 3166459937, 1852735737, 3680868867, 612352556, 2760189833, 3816750341, 699140493, 1087846865, 394927937, 2063539671, 645417889, 2337669049, 3773167612, 678121169, 3006984620, 1163491294, 2559287860, 543155592, 3194181347, 2463543297, 3875146860, 475483913, 3707568076, 3881808875, 1264657097, 208126250, 1802809301, 367907560, 2433375693, 2851326449, 2380707878, 2911758972, 4243386879, 2229228726, 828161871, 2871116151, 990638198, 178193628, 1012573979, 1223581943, 3333023583, 1901888414, 3913876750, 3168662389, 656194888, 1553610174, 466840498, 686407570, 280737523, 2476489017, 1272981410, 3189431979, 3294710282, 1564477163, 4133221553, 823708826, 880616227, 1730254897, 335723347, 2123911971, 344194767, 119099153, 2915257116, 3339825470, 2524942970, 1191117250, 3403812186, 3988972937, 2575395295, 4072737183, 663832315, 808080503, 724042340, 2966189542, 2499643239, 3309205581, 1915303227, 72616536, 387525935, 2791701251, 2190905566, 3740328774, 831297460, 3750964864, 2190112044, 899144100, 2346558003, 3851695829, 2896963823, 1548614403, 3676707405, 2050891594, 4165893148, 1883017153, 2668787527, 50330561, 2063572142, 1853585557, 1716111087, 2937248370, 1650859709, 2682305722, 565243175, 3922227187, 3482032705, 2809081500, 2099376873, 230358556, 1065827745, 196966939, 3268845630, 3625508265, 1477799595, 4149453740, 2757835686, 3032697936, 2200108791, 3421680711, 4145382259, 3605253072, 1186485728, 3520482151, 3080733463, 3887314157, 4030447755, 1699987022, 1393253586, 1710066407, 710337383, 3754612557, 2741088369, 337455371, 1304761604, 3592681639, 3099385187, 4003676405, 317081535, 997754381, 480565460, 3806265432, 1068029852, 776179010, 470617537, 3653875421, 2273571919, 1055365147, 1317172834, 3414733003, 2835400613, 28845217, 631741764, 2334552212, 3565466095, 1225096926, 1277781438, 2416008223, 1268768054, 2750789241, 267768398, 2175383438, 268654341, 2550530755, 2971623408, 1666669894, 1934871760, 509782083, 2798468670, 2834016892, 2494149255, 1965005899, 2653045765, 2317194903, 1297426078, 916214929, 2967861004, 2236807006, 2476725285, 128488253, 4277714156, 3016192551, 1690883702, 1329810641, 593010415, 2341313579, 1754238478, 1242698701, 2152594527, 2103269013, 926178633, 647225267, 4243787142, 1489208161, 3188798921, 1327553793, 3644600811, 684513652, 2606555057, 2705329549, 2557469018, 1294205096, 70104222, 3020083528, 2015571237, 2768573480, 401698695, 2812362809, 328919870, 984940142, 1653817439, 471643152, 538942283, 2040555667, 1211982999, 1663497772, 2941793728, 3001026698, 313271977, 3644502703, 2423950047, 2629046069, 3450826936, 44600781, 2633869288, 4267014746, 4204914470, 1955987363, 2590608885, 2120168063, 1460034243, 258056600, 3693550087, 779446436, 902696389, 4228701387, 3165791227, 3478614865, 1500865135, 905884796, 3682046467, 2437847832, 2595888219, 4144484663, 1299603103, 648536946, 1762836247, 4265749196, 950840266, 2928992722, 2051369009, 2071186450, 1164619682, 210405235, 1296628868, 2425474719, 4083386904, 1978331343, 3190898799, 602128683, 2003319330, 1043377147, 756690484, 24776626, 1835824233, 1156421176, 2125448878, 1333136189, 607751135, 4255614767, 4238533009, 2583175632, 230472465, 3037259757, 1546348932, 2537279411, 110471952, 520621708, 63613561, 2843673595, 775036, 1899744556, 1168115970, 2685086321, 3410250658, 3151102153, 634647644, 3639125394, 3344624764, 1525171811, 1878800371, 3356530116, 3676542926, 602053165, 2686708238, 3703555082, 3754961372, 3970030923, 1749014201, 3391107050, 2478152000, 2121779806, 2636689360, 769835312, 4230539591, 1909812524, 417081626, 3096519324, 387659697, 3764499249, 3452925463, 3818277698, 3008920324, 15253694, 1479260759, 2421328720, 2220743357, 38831551, 1032912064, 3400956198, 2362808832, 3988706866, 1950464958, 3248573125, 1225815945, 1211036180, 346407094, 3867176764, 1257086026, 2725236231, 2843735658, 4147241082, 1729974832, 1256499145, 3765975901, 784776076, 4288277427, 3903532520, 3431522864, 2792589977, 2935989154, 3536596892, 3512984120, 605476293, 1774961976, 981422589, 822525778, 3343539932, 422954622, 1323482938, 2523465420, 2746609356, 1664448205, 272567300, 711582493, 3625722107, 3615865699, 950619756, 2864168489, 108006277, 3976313352, 680217319, 173747636, 291134870, 198587329, 595310009, 941470866, 2438488368, 1681923153, 1654783272, 3531789254, 4149541715, 2922706987, 684907209, 3116688362, 3288142886, 3953377592, 3332428007, 1400401813, 3745921798, 1701705628, 3744511893, 1838265811, 3314032512, 3894840150, 3810031409, 181324387, 983160249, 1444959400, 3836664153, 3032673327, 310789231, 3701565562, 1407580781, 2511575629, 3113822685, 1777261998, 2208898751, 106383174, 2961020500, 995776421, 3306087121, 2181030035, 2300064751, 1909543740, 4023156173, 1671619075, 2151956104, 237668401, 3204511253, 1303668692, 3868259787, 2737897899, 4091026033, 2877780671, 134376279, 398912026, 863520778, 3712468923, 3443213666, 2183809552, 2597379302, 349776833, 274697715, 4266593710, 4282186769, 3530757867, 520237914, 3369037397, 2285670338, 387086485, 618942879, 219892882, 2008897906, 2293749560, 2907436476, 3853296593, 327550390, 1558751403, 2125694704, 1822570484, 2409968265, 436622776, 2691124090, 1080819771, 2958107334, 2667158841, 2117901613, 440045635, 3861104471, 3574962701, 3210299248, 1368601573, 2434039520, 86704919, 3628108033, 1909858745, 227461000, 2530509465, 838433817, 730224848, 1060658180, 1318482825, 233266846, 2352800845, 2086493219, 3826355555, 3174377690, 1455208243, 1356597942, 663563056, 2501819374, 4213535259, 1585241464, 873997246, 2597898744, 427064229, 1587746589, 259660817, 1688808891, 4165834345, 1359025114, 2013923952, 2963511711, 2903220732, 356112706, 501549847, 1609412897, 1685128111, 2639303606, 700554261, 914150235, 2010650618, 2029243163, 3046509911, 715702687, 2206956754, 3045298216, 2922667179, 2497577415, 3001819604, 706666890, 2275923855, 3094184383, 2781697712, 3292952666, 4238614078, 278500659, 1440033346, 1552714131, 336554687, 2842580609, 2255044310, 2180071372, 99970159, 2078552309, 1172694639, 1359399314, 546452524, 349053834, 3072254369, 3043246719, 3314426498, 1594992663, 3582269665, 2114045278, 585873328, 840739494, 3475778485, 1506518790, 4008486652, 229989333, 3582278212, 363921215, 3592842520, 1833533669, 708173875, 564248927, 853943228, 2282731374, 2874158047, 3978663285, 2332696531, 1354524859, 58121641, 1445193461, 1936635021, 3374328198, 3465253060, 385589199, 1819596280, 912895627, 1877426726, 733280947, 2004202992, 3311780711, 3732053191, 309903272, 97290141, 2945419335, 3916477072, 1326195031, 3740938055, 3604745262, 3633308956, 3392929431, 1257547457, 251825182, 3318700085, 847033774, 137350663, 1716455973, 546850455, 4227574519, 3044214953, 2259874013, 2442748258, 2956971336, 2198772379, 1269686727, 2648116105, 1339159363, 1473334647, 2386671612, 2069268389],
                                624,
                                0,
                                0.0
                            ],
                            "steps": [
                                [
                                    "data_preprocessing",
                                    {
                                        "@value": {
                                            "type": "autosklearn.pipeline.components.data_preprocessing.data_preprocessing.DataPreprocessor",
                                            "params": {
                                                "categorical_features": null,
                                                "config": null,
                                                "dataset_properties": null,
                                                "exclude": null,
                                                "force_sparse_output": null,
                                                "include": null,
                                                "init_params": null,
                                                "pipeline": null,
                                                "random_state": null
                                            }
                                        }
                                    }
                                ],
                                [
                                    "balancing",
                                    {
                                        "@value": {
                                            "type": "autosklearn.pipeline.components.data_preprocessing.balancing.balancing.Balancing",
                                            "params": {
                                                "random_state": null,
                                                "strategy": "none"
                                            }
                                        }
                                    }
                                ],
                                [
                                    "feature_preprocessor",
                                    {
                                        "densifier": "Densifier",
                                        "extra_trees_preproc_for_classification": "ExtraTreesPreprocessorClassification",
                                        "extra_trees_preproc_for_regression": "ExtraTreesPreprocessorRegression",
                                        "fast_ica": "FastICA",
                                        "feature_agglomeration": "FeatureAgglomeration",
                                        "kernel_pca": "KernelPCA",
                                        "kitchen_sinks": "RandomKitchenSinks",
                                        "liblinear_svc_preprocessor": "LibLinear_Preprocessor",
                                        "no_preprocessing": "NoPreprocessing",
                                        "nystroem_sampler": "Nystroem",
                                        "pca": "PCA",
                                        "polynomial": "PolynomialFeatures",
                                        "random_trees_embedding": "RandomTreesEmbedding",
                                        "select_percentile_classification": "SelectPercentileClassification",
                                        "select_percentile_regression": "SelectPercentileRegression",
                                        "select_rates": "SelectRates",
                                        "truncatedSVD": "TruncatedSVD"
                                    }
                                ],
                                [
                                    "classifier",
                                    {
                                        "adaboost": "AdaboostClassifier",
                                        "bernoulli_nb": "BernoulliNB",
                                        "decision_tree": "DecisionTree",
                                        "extra_trees": "ExtraTreesClassifier",
                                        "gaussian_nb": "GaussianNB",
                                        "gradient_boosting": "GradientBoostingClassifier",
                                        "k_nearest_neighbors": "KNearestNeighborsClassifier",
                                        "lda": "LDA",
                                        "liblinear_svc": "LibLinear_SVC",
                                        "libsvm_svc": "LibSVM_SVC",
                                        "multinomial_nb": "MultinomialNB",
                                        "passive_aggressive": "PassiveAggressive",
                                        "qda": "QDA",
                                        "random_forest": "RandomForest",
                                        "sgd": "SGD"
                                    }
                                ]
                            ],
                            "data_preprocessing": {
                                "@value": {
                                    "type": "autosklearn.pipeline.components.data_preprocessing.data_preprocessing.DataPreprocessor",
                                    "params": {
                                        "categorical_features": null,
                                        "config": null,
                                        "dataset_properties": null,
                                        "exclude": null,
                                        "force_sparse_output": null,
                                        "include": null,
                                        "init_params": null,
                                        "pipeline": null,
                                        "random_state": null
                                    }
                                }
                            },
                            "balancing": {
                                "@value": {
                                    "type": "autosklearn.pipeline.components.data_preprocessing.balancing.balancing.Balancing",
                                    "params": {
                                        "random_state": null,
                                        "strategy": "none"
                                    }
                                }
                            },
                            "feature_preprocessor": {
                                "densifier": "Densifier",
                                "extra_trees_preproc_for_classification": "ExtraTreesPreprocessorClassification",
                                "extra_trees_preproc_for_regression": "ExtraTreesPreprocessorRegression",
                                "fast_ica": "FastICA",
                                "feature_agglomeration": "FeatureAgglomeration",
                                "kernel_pca": "KernelPCA",
                                "kitchen_sinks": "RandomKitchenSinks",
                                "liblinear_svc_preprocessor": "LibLinear_Preprocessor",
                                "no_preprocessing": "NoPreprocessing",
                                "nystroem_sampler": "Nystroem",
                                "pca": "PCA",
                                "polynomial": "PolynomialFeatures",
                                "random_trees_embedding": "RandomTreesEmbedding",
                                "select_percentile_classification": "SelectPercentileClassification",
                                "select_percentile_regression": "SelectPercentileRegression",
                                "select_rates": "SelectRates",
                                "truncatedSVD": "TruncatedSVD"
                            },
                            "classifier": {
                                "adaboost": "AdaboostClassifier",
                                "bernoulli_nb": "BernoulliNB",
                                "decision_tree": "DecisionTree",
                                "extra_trees": "ExtraTreesClassifier",
                                "gaussian_nb": "GaussianNB",
                                "gradient_boosting": "GradientBoostingClassifier",
                                "k_nearest_neighbors": "KNearestNeighborsClassifier",
                                "lda": "LDA",
                                "liblinear_svc": "LibLinear_SVC",
                                "libsvm_svc": "LibSVM_SVC",
                                "multinomial_nb": "MultinomialNB",
                                "passive_aggressive": "PassiveAggressive",
                                "qda": "QDA",
                                "random_forest": "RandomForest",
                                "sgd": "SGD"
                            },
                            "data_preprocessing__categorical_features": null,
                            "data_preprocessing__config": null,
                            "data_preprocessing__dataset_properties": null,
                            "data_preprocessing__exclude": null,
                            "data_preprocessing__force_sparse_output": null,
                            "data_preprocessing__include": null,
                            "data_preprocessing__init_params": null,
                            "data_preprocessing__pipeline": null,
                            "data_preprocessing__random_state": null,
                            "balancing__random_state": null,
                            "balancing__strategy": "none"
                        }
                    }
                }
            ],
            "specified_by": {
                "@id": "_:automl"
            },
            "@type": "mls:ModelEvaluation"
        }
    ],
    "realizes": null,
    "version": null,
    "name": null,
    "@context": {
        "mls": "http://www.w3.org/ns/mls#",
        "@version": 1.1,
        "_id": "@id",
        "dcterms": "http://purl.org/dc/terms/",
        "executes": {
            "@id": "mls:executes",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "dcterms": "http://purl.org/dc/terms/",
                "name": "dcterms:title",
                "parameters": {
                    "@id": "mls:hasHyperParameter",
                    "@context": {
                        "mls": "http://www.w3.org/ns/mls#",
                        "@version": 1.1,
                        "_id": "@id"
                    }
                },
                "implements": {
                    "@id": "mls:implements",
                    "@context": {
                        "mls": "http://www.w3.org/ns/mls#",
                        "@version": 1.1,
                        "_id": "@id"
                    }
                },
                "version": "dcterms:hasVersion"
            }
        },
        "input_values": {
            "@id": "mls:hasInput",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "xsd": "http://www.w3.org/2001/XMLSchema#",
                "specified_by": "mls:specifiedBy",
                "value": "mls:hasValue"
            }
        },
        "output_values": {
            "@id": "mls:hasOutput",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "xsd": "http://www.w3.org/2001/XMLSchema#",
                "specified_by": "mls:specifiedBy",
                "value": "mls:hasValue"
            }
        },
        "realizes": {
            "@id": "mls:implements",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id"
            }
        },
        "version": "dcterms:hasVersion",
        "name": "dcterms:title"
    },
    "@type": "mls:Run"
}
chrisbarber commented 4 years ago

And heres a diff since I didn't create a branch https://github.com/ratschlab/mlschema-model-converters/compare/ec4817c..master

vigsterkr commented 4 years ago

yeah its a good start but these things need to be normalized to the schema, meaning that the output values has to be representing HyperParameterSettings if you know what i mean. coz there we have a full machine that has HyperParameter and HyperParameterSettings. i'll try to use the dumped json to show what i mean above

vigsterkr commented 4 years ago

btw if you would do a PR then i could add there some more comments as well

chrisbarber commented 4 years ago

yeah its a good start but these things need to be normalized to the schema, meaning that the output values has to be representing HyperParameterSettings if you know what i mean. coz there we have a full machine that has HyperParameter and HyperParameterSettings. i'll try to use the dumped json to show what i mean above

I just randomly guessed using ModelEvaluation. If it's as simple as switching that to HyperParameterSettings like with the .input_values I can do that; otherwise yeah I guess I will need some explanation

vigsterkr commented 4 years ago

ok so let's take this part of the generated json:

   "classifier:random_forest:bootstrap": "True",
                                "classifier:random_forest:criterion": "gini",
                                "classifier:random_forest:max_depth": "None",
                                "classifier:random_forest:max_features": 0.5,
                                "classifier:random_forest:max_leaf_nodes": "None",
                                "classifier:random_forest:min_impurity_decrease": 0.0,
                                "classifier:random_forest:min_samples_leaf": 1,
                                "classifier:random_forest:min_samples_split": 2,
                                "classifier:random_forest:min_weight_fraction_leaf": 0.0,

so this is basically the HyperParameterSetting of a sklearn RandomForest. if you run the converter on a simple sklearn RF you would get something like this:

{
    "identifier": "a9156457-114e-4dea-9dfa-37f2b3a587df",
    "executes": {
        "_id": "_:sklearn.ensemble._forest.RandomForestClassifier",
        "identifier": "aac39ab5-c124-4b84-bf85-d36c2d925c56",
        "name": null,
        "parameters": [{
            "_id": "_:bootstrap",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:ccp_alpha",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:class_weight",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:criterion",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:max_depth",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:max_features",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:max_leaf_nodes",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:max_samples",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:min_impurity_decrease",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:min_impurity_split",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:min_samples_leaf",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:min_samples_split",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:min_weight_fraction_leaf",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:n_estimators",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:n_jobs",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:oob_score",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:random_state",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:verbose",
            "@type": "mls:HyperParameter"
        }, {
            "_id": "_:warm_start",
            "@type": "mls:HyperParameter"
        }],
        "implements": {
            "_id": "_:sklearn.ensemble._forest.RandomForestClassifier",
            "@type": "mls:Algorithm"
        },
        "version": null,
        "@type": "mls:Implementation"
    },
    "input_values": [{
        "value": {
            "@type": "xsd:boolean",
            "@value": true
        },
        "specified_by": {
            "@id": "_:bootstrap"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:float",
            "@value": 0.0
        },
        "specified_by": {
            "@id": "_:ccp_alpha"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:class_weight"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:string",
            "@value": "entropy"
        },
        "specified_by": {
            "@id": "_:criterion"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:max_depth"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:string",
            "@value": "auto"
        },
        "specified_by": {
            "@id": "_:max_features"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:max_leaf_nodes"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:max_samples"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:float",
            "@value": 0.0
        },
        "specified_by": {
            "@id": "_:min_impurity_decrease"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:min_impurity_split"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:int",
            "@value": 1
        },
        "specified_by": {
            "@id": "_:min_samples_leaf"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:int",
            "@value": 2
        },
        "specified_by": {
            "@id": "_:min_samples_split"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:float",
            "@value": 0.0
        },
        "specified_by": {
            "@id": "_:min_weight_fraction_leaf"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:int",
            "@value": 1
        },
        "specified_by": {
            "@id": "_:n_estimators"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:n_jobs"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:boolean",
            "@value": false
        },
        "specified_by": {
            "@id": "_:oob_score"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:anyURI",
            "@value": null
        },
        "specified_by": {
            "@id": "_:random_state"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:int",
            "@value": 0
        },
        "specified_by": {
            "@id": "_:verbose"
        },
        "@type": "mls:HyperParameterSetting"
    }, {
        "value": {
            "@type": "xsd:boolean",
            "@value": false
        },
        "specified_by": {
            "@id": "_:warm_start"
        },
        "@type": "mls:HyperParameterSetting"
    }],
    "output_values": [{
        "_id": "_:accuracy_score1892606500",
        "value": {
            "@type": "xsd:double",
            "@value": 0.864406779661017
        },
        "specified_by": {
            "_id": "http://www.w3.org/ns/mls#accuracy",
            "@type": "mls:EvaluationMeasure"
        },
        "@type": "mls:ModelEvaluation"
    }],
    "realizes": {
        "_id": "_:sklearn.ensemble._forest.RandomForestClassifier",
        "@type": "mls:Algorithm"
    },
    "version": null,
    "name": null,
    "@context": {
        "mls": "http://www.w3.org/ns/mls#",
        "@version": 1.1,
        "_id": "@id",
        "dcterms": "http://purl.org/dc/terms/",
        "executes": {
            "@id": "mls:executes",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "dcterms": "http://purl.org/dc/terms/",
                "name": "dcterms:title",
                "parameters": {
                    "@id": "mls:hasHyperParameter",
                    "@context": {
                        "mls": "http://www.w3.org/ns/mls#",
                        "@version": 1.1,
                        "_id": "@id"
                    }
                },
                "implements": {
                    "@id": "mls:implements",
                    "@context": {
                        "mls": "http://www.w3.org/ns/mls#",
                        "@version": 1.1,
                        "_id": "@id"
                    }
                },
                "version": "dcterms:hasVersion"
            }
        },
        "input_values": {
            "@id": "mls:hasInput",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "xsd": "http://www.w3.org/2001/XMLSchema#",
                "specified_by": "mls:specifiedBy",
                "value": "mls:hasValue"
            }
        },
        "output_values": {
            "@id": "mls:hasOutput",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id",
                "xsd": "http://www.w3.org/2001/XMLSchema#",
                "specified_by": "mls:specifiedBy",
                "value": "mls:hasValue"
            }
        },
        "realizes": {
            "@id": "mls:implements",
            "@context": {
                "mls": "http://www.w3.org/ns/mls#",
                "@version": 1.1,
                "_id": "@id"
            }
        },
        "version": "dcterms:hasVersion",
        "name": "dcterms:title"
    },
    "@type": "mls:Run"
}

so the idea is that the first one i've quoted should be formulated something like above namely have an Implementation and that has it's HyperParamaters which will have their HyperParameterSettings...

and similarly to all the other sklearn components in the pipeline

chrisbarber commented 4 years ago

what's the status of mlschema? is it possible to programmatically validate against it yet?

vigsterkr commented 4 years ago

afaik there's currently no json schema defined over it, nor xmlschema.

chrisbarber commented 4 years ago

@vigsterkr can you tell me if you like this json. this does two things:

  1. considers everything that responds to get_params as an mls Run and all the params as HyperParameterSettings. if things are not Run's then i guess i need to know what they are.

  2. takes that Configuration from autosklearn and instantiates a dummy sklearn model according to it, so it can be converted to the corresponding mls. right now this is hacked-in (hard coded for random forest for this example); want to confirm before generalizing

json ```json { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.automl.AutoML", "identifier": "ba9de1b0-22a9-494a-82c7-68f429d5585e", "implements": { "@type": "mls:Algorithm", "_id": "_:autosklearn.automl.AutoML" }, "name": null, "parameters": [ { "@type": "mls:HyperParameter", "_id": "_:identifier" }, { "@type": "mls:HyperParameter", "_id": "_:executes" }, { "@type": "mls:HyperParameter", "_id": "_:input_values" }, { "@type": "mls:HyperParameter", "_id": "_:output_values" }, { "@type": "mls:HyperParameter", "_id": "_:realizes" }, { "@type": "mls:HyperParameter", "_id": "_:version" }, { "@type": "mls:HyperParameter", "_id": "_:name" }, { "@type": "mls:HyperParameter", "_id": "_:@context" }, { "@type": "mls:HyperParameter", "_id": "_:@type" } ], "version": null }, "identifier": "68d04b43-726b-400f-b7b9-9eab5ab2cc53", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:identifier" }, "value": "5623e3e1-5b80-48c4-a49d-2fa3c369a265" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:executes" }, "value": { "@type": "mls:Implementation", "_id": "_:autosklearn.automl.AutoML", "identifier": "b1dfb41b-fb09-4ee1-8dcc-694362d71444", "implements": null, "name": null, "parameters": [], "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:input_values" }, "value": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:precision" }, "value": 32 } ] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:output_values" }, "value": [] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@context" }, "value": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@type" }, "value": "mls:Run" } ], "name": null, "output_values": [ { "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.classification.SimpleClassificationPipeline", "identifier": "e8ec79b7-a330-45e1-a4d2-991af73b51c7", "implements": { "@type": "mls:Algorithm", "_id": "_:autosklearn.pipeline.classification.SimpleClassificationPipeline" }, "name": null, "parameters": [ { "@type": "mls:HyperParameter", "_id": "_:identifier" }, { "@type": "mls:HyperParameter", "_id": "_:executes" }, { "@type": "mls:HyperParameter", "_id": "_:input_values" }, { "@type": "mls:HyperParameter", "_id": "_:output_values" }, { "@type": "mls:HyperParameter", "_id": "_:realizes" }, { "@type": "mls:HyperParameter", "_id": "_:version" }, { "@type": "mls:HyperParameter", "_id": "_:name" }, { "@type": "mls:HyperParameter", "_id": "_:@context" }, { "@type": "mls:HyperParameter", "_id": "_:@type" } ], "version": null }, "identifier": "87fc8496-72cf-47b3-bcc5-e10a08a5bd33", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:identifier" }, "value": "d82c3d31-4df0-4d1f-9d25-4640f7cbd247" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:executes" }, "value": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.classification.SimpleClassificationPipeline", "identifier": "3672f062-c7ea-4722-91df-4a835a1347cd", "implements": null, "name": null, "parameters": [], "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:input_values" }, "value": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:config" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:sklearn.ensemble._forest.RandomForestClassifier", "identifier": "98ac96c7-6c6f-4b26-8f40-3f4915e45966", "implements": { "@type": "mls:Algorithm", "_id": "_:sklearn.ensemble._forest.RandomForestClassifier" }, "name": null, "parameters": [ { "@type": "mls:HyperParameter", "_id": "_:identifier" }, { "@type": "mls:HyperParameter", "_id": "_:executes" }, { "@type": "mls:HyperParameter", "_id": "_:input_values" }, { "@type": "mls:HyperParameter", "_id": "_:output_values" }, { "@type": "mls:HyperParameter", "_id": "_:realizes" }, { "@type": "mls:HyperParameter", "_id": "_:version" }, { "@type": "mls:HyperParameter", "_id": "_:name" }, { "@type": "mls:HyperParameter", "_id": "_:@context" }, { "@type": "mls:HyperParameter", "_id": "_:@type" } ], "version": null }, "identifier": "8ec0615a-6639-42c5-af2b-474dfd5ccccb", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:identifier" }, "value": "9e31545a-f1a3-4978-a55e-07fd93459a00" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:executes" }, "value": { "@type": "mls:Implementation", "_id": "_:sklearn.ensemble._forest.RandomForestClassifier", "identifier": "a27b36fe-c36d-424e-a8a5-d51179965db6", "implements": null, "name": null, "parameters": [], "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:input_values" }, "value": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:bootstrap" }, "value": "True" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:ccp_alpha" }, "value": 0.0 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:criterion" }, "value": "gini" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:max_depth" }, "value": "None" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:max_features" }, "value": 0.5 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:max_leaf_nodes" }, "value": "None" }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:min_impurity_decrease" }, "value": 0.0 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:min_samples_leaf" }, "value": 1 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:min_samples_split" }, "value": 2 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:min_weight_fraction_leaf" }, "value": 0.0 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:n_estimators" }, "value": 100 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:oob_score" }, "value": false }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:verbose" }, "value": 0 }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:warm_start" }, "value": false } ] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:output_values" }, "value": [] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@context" }, "value": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@type" }, "value": "mls:Run" } ], "name": null, "output_values": [], "realizes": null, "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:dataset_properties" }, "value": { "multiclass": true, "multilabel": false, "signed": false, "sparse": false, "target_type": "classification", "task": 2 } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:exclude" }, "value": {} }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:include" }, "value": {} }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:init_params" }, "value": { "instance": "{\"task_id\": \"e5941b9de02ebe2c0457a6ec6eb35c17\"}" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:random_state" }, "value": [ "MT19937", [ 1, 1812433254, 3713160357, 3109174145, 64984499, 3392658084, 446538473, 2629760756, 2453345558, 1394803949, 1021787430, 2063496713, 1304877364, 1713639158, 889001601, 1651239412, 1450863289, 745575081, 361057727, 2288771950, 1463387568, 2249488362, 26637982, 204036717, 1655702041, 1329048465, 2092351466, 1681619666, 3220660315, 1301783610, 626286181, 294669048, 3537128440, 3259518248, 2550101273, 1160881866, 308703547, 295714668, 35508674, 1599247281, 376272024, 3166459937, 1852735737, 3680868867, 612352556, 2760189833, 3816750341, 699140493, 1087846865, 394927937, 2063539671, 645417889, 2337669049, 3773167612, 678121169, 3006984620, 1163491294, 2559287860, 543155592, 3194181347, 2463543297, 3875146860, 475483913, 3707568076, 3881808875, 1264657097, 208126250, 1802809301, 367907560, 2433375693, 2851326449, 2380707878, 2911758972, 4243386879, 2229228726, 828161871, 2871116151, 990638198, 178193628, 1012573979, 1223581943, 3333023583, 1901888414, 3913876750, 3168662389, 656194888, 1553610174, 466840498, 686407570, 280737523, 2476489017, 1272981410, 3189431979, 3294710282, 1564477163, 4133221553, 823708826, 880616227, 1730254897, 335723347, 2123911971, 344194767, 119099153, 2915257116, 3339825470, 2524942970, 1191117250, 3403812186, 3988972937, 2575395295, 4072737183, 663832315, 808080503, 724042340, 2966189542, 2499643239, 3309205581, 1915303227, 72616536, 387525935, 2791701251, 2190905566, 3740328774, 831297460, 3750964864, 2190112044, 899144100, 2346558003, 3851695829, 2896963823, 1548614403, 3676707405, 2050891594, 4165893148, 1883017153, 2668787527, 50330561, 2063572142, 1853585557, 1716111087, 2937248370, 1650859709, 2682305722, 565243175, 3922227187, 3482032705, 2809081500, 2099376873, 230358556, 1065827745, 196966939, 3268845630, 3625508265, 1477799595, 4149453740, 2757835686, 3032697936, 2200108791, 3421680711, 4145382259, 3605253072, 1186485728, 3520482151, 3080733463, 3887314157, 4030447755, 1699987022, 1393253586, 1710066407, 710337383, 3754612557, 2741088369, 337455371, 1304761604, 3592681639, 3099385187, 4003676405, 317081535, 997754381, 480565460, 3806265432, 1068029852, 776179010, 470617537, 3653875421, 2273571919, 1055365147, 1317172834, 3414733003, 2835400613, 28845217, 631741764, 2334552212, 3565466095, 1225096926, 1277781438, 2416008223, 1268768054, 2750789241, 267768398, 2175383438, 268654341, 2550530755, 2971623408, 1666669894, 1934871760, 509782083, 2798468670, 2834016892, 2494149255, 1965005899, 2653045765, 2317194903, 1297426078, 916214929, 2967861004, 2236807006, 2476725285, 128488253, 4277714156, 3016192551, 1690883702, 1329810641, 593010415, 2341313579, 1754238478, 1242698701, 2152594527, 2103269013, 926178633, 647225267, 4243787142, 1489208161, 3188798921, 1327553793, 3644600811, 684513652, 2606555057, 2705329549, 2557469018, 1294205096, 70104222, 3020083528, 2015571237, 2768573480, 401698695, 2812362809, 328919870, 984940142, 1653817439, 471643152, 538942283, 2040555667, 1211982999, 1663497772, 2941793728, 3001026698, 313271977, 3644502703, 2423950047, 2629046069, 3450826936, 44600781, 2633869288, 4267014746, 4204914470, 1955987363, 2590608885, 2120168063, 1460034243, 258056600, 3693550087, 779446436, 902696389, 4228701387, 3165791227, 3478614865, 1500865135, 905884796, 3682046467, 2437847832, 2595888219, 4144484663, 1299603103, 648536946, 1762836247, 4265749196, 950840266, 2928992722, 2051369009, 2071186450, 1164619682, 210405235, 1296628868, 2425474719, 4083386904, 1978331343, 3190898799, 602128683, 2003319330, 1043377147, 756690484, 24776626, 1835824233, 1156421176, 2125448878, 1333136189, 607751135, 4255614767, 4238533009, 2583175632, 230472465, 3037259757, 1546348932, 2537279411, 110471952, 520621708, 63613561, 2843673595, 775036, 1899744556, 1168115970, 2685086321, 3410250658, 3151102153, 634647644, 3639125394, 3344624764, 1525171811, 1878800371, 3356530116, 3676542926, 602053165, 2686708238, 3703555082, 3754961372, 3970030923, 1749014201, 3391107050, 2478152000, 2121779806, 2636689360, 769835312, 4230539591, 1909812524, 417081626, 3096519324, 387659697, 3764499249, 3452925463, 3818277698, 3008920324, 15253694, 1479260759, 2421328720, 2220743357, 38831551, 1032912064, 3400956198, 2362808832, 3988706866, 1950464958, 3248573125, 1225815945, 1211036180, 346407094, 3867176764, 1257086026, 2725236231, 2843735658, 4147241082, 1729974832, 1256499145, 3765975901, 784776076, 4288277427, 3903532520, 3431522864, 2792589977, 2935989154, 3536596892, 3512984120, 605476293, 1774961976, 981422589, 822525778, 3343539932, 422954622, 1323482938, 2523465420, 2746609356, 1664448205, 272567300, 711582493, 3625722107, 3615865699, 950619756, 2864168489, 108006277, 3976313352, 680217319, 173747636, 291134870, 198587329, 595310009, 941470866, 2438488368, 1681923153, 1654783272, 3531789254, 4149541715, 2922706987, 684907209, 3116688362, 3288142886, 3953377592, 3332428007, 1400401813, 3745921798, 1701705628, 3744511893, 1838265811, 3314032512, 3894840150, 3810031409, 181324387, 983160249, 1444959400, 3836664153, 3032673327, 310789231, 3701565562, 1407580781, 2511575629, 3113822685, 1777261998, 2208898751, 106383174, 2961020500, 995776421, 3306087121, 2181030035, 2300064751, 1909543740, 4023156173, 1671619075, 2151956104, 237668401, 3204511253, 1303668692, 3868259787, 2737897899, 4091026033, 2877780671, 134376279, 398912026, 863520778, 3712468923, 3443213666, 2183809552, 2597379302, 349776833, 274697715, 4266593710, 4282186769, 3530757867, 520237914, 3369037397, 2285670338, 387086485, 618942879, 219892882, 2008897906, 2293749560, 2907436476, 3853296593, 327550390, 1558751403, 2125694704, 1822570484, 2409968265, 436622776, 2691124090, 1080819771, 2958107334, 2667158841, 2117901613, 440045635, 3861104471, 3574962701, 3210299248, 1368601573, 2434039520, 86704919, 3628108033, 1909858745, 227461000, 2530509465, 838433817, 730224848, 1060658180, 1318482825, 233266846, 2352800845, 2086493219, 3826355555, 3174377690, 1455208243, 1356597942, 663563056, 2501819374, 4213535259, 1585241464, 873997246, 2597898744, 427064229, 1587746589, 259660817, 1688808891, 4165834345, 1359025114, 2013923952, 2963511711, 2903220732, 356112706, 501549847, 1609412897, 1685128111, 2639303606, 700554261, 914150235, 2010650618, 2029243163, 3046509911, 715702687, 2206956754, 3045298216, 2922667179, 2497577415, 3001819604, 706666890, 2275923855, 3094184383, 2781697712, 3292952666, 4238614078, 278500659, 1440033346, 1552714131, 336554687, 2842580609, 2255044310, 2180071372, 99970159, 2078552309, 1172694639, 1359399314, 546452524, 349053834, 3072254369, 3043246719, 3314426498, 1594992663, 3582269665, 2114045278, 585873328, 840739494, 3475778485, 1506518790, 4008486652, 229989333, 3582278212, 363921215, 3592842520, 1833533669, 708173875, 564248927, 853943228, 2282731374, 2874158047, 3978663285, 2332696531, 1354524859, 58121641, 1445193461, 1936635021, 3374328198, 3465253060, 385589199, 1819596280, 912895627, 1877426726, 733280947, 2004202992, 3311780711, 3732053191, 309903272, 97290141, 2945419335, 3916477072, 1326195031, 3740938055, 3604745262, 3633308956, 3392929431, 1257547457, 251825182, 3318700085, 847033774, 137350663, 1716455973, 546850455, 4227574519, 3044214953, 2259874013, 2442748258, 2956971336, 2198772379, 1269686727, 2648116105, 1339159363, 1473334647, 2386671612, 2069268389 ], 624, 0, 0.0 ] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:steps" }, "value": [ [ "data_preprocessing", { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.data_preprocessing.data_preprocessing.DataPreprocessor", "identifier": "bad61a7a-11b8-4058-ba15-211cbada773d", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "826a63b2-1b93-45b5-91b5-7fff321fa8fc", "input_values": [], "name": null, "output_values": [], "realizes": null, "version": null } ], [ "balancing", { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.data_preprocessing.balancing.balancing.Balancing", "identifier": "f4ef0587-6abb-45cc-9ae8-188a0f8e3627", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "aed123c6-0edb-479c-88ba-638d8d8c5dce", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:strategy" }, "value": "none" } ], "name": null, "output_values": [], "realizes": null, "version": null } ], [ "feature_preprocessor", { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.feature_preprocessing.FeaturePreprocessorChoice", "identifier": "8a3260b1-2b45-4323-917e-30baf3b455e9", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "9ab41414-fe9a-4910-a0df-67e445b4cdd3", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:densifier" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "Densifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees_preproc_for_classification" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesPreprocessorClassification" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees_preproc_for_regression" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesPreprocessorRegression" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:fast_ica" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "FastICA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:feature_agglomeration" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "FeatureAgglomeration" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:kernel_pca" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "KernelPCA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:kitchen_sinks" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomKitchenSinks" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:liblinear_svc_preprocessor" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibLinear_Preprocessor" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:no_preprocessing" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "NoPreprocessing" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:nystroem_sampler" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "Nystroem" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:pca" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PCA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:polynomial" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PolynomialFeatures" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:random_trees_embedding" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomTreesEmbedding" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_percentile_classification" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectPercentileClassification" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_percentile_regression" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectPercentileRegression" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_rates" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectRates" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:truncatedSVD" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "TruncatedSVD" } } ], "name": null, "output_values": [], "realizes": null, "version": null } ], [ "classifier", { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.classification.ClassifierChoice", "identifier": "61a235c6-2278-4057-913c-71c11b2753a5", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "22f9911c-9bcd-42d2-8881-95d181ed0a18", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:adaboost" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "AdaboostClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:bernoulli_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "BernoulliNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:decision_tree" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "DecisionTree" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:gaussian_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "GaussianNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:gradient_boosting" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "GradientBoostingClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:k_nearest_neighbors" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "KNearestNeighborsClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:lda" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LDA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:liblinear_svc" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibLinear_SVC" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:libsvm_svc" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibSVM_SVC" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:multinomial_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "MultinomialNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:passive_aggressive" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PassiveAggressive" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:qda" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "QDA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:random_forest" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomForest" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:sgd" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SGD" } } ], "name": null, "output_values": [], "realizes": null, "version": null } ] ] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:data_preprocessing" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.data_preprocessing.data_preprocessing.DataPreprocessor", "identifier": "ebbcf6e4-9110-4217-9465-3f55b44fa900", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "9878366c-b2fa-4843-909e-dff09490d5fd", "input_values": [], "name": null, "output_values": [], "realizes": null, "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:balancing" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.data_preprocessing.balancing.balancing.Balancing", "identifier": "9b85c49e-14f3-4d6e-952e-3dc582f774b4", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "d1116c3c-bbd7-4570-9f67-12b71b8d6e2f", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:strategy" }, "value": "none" } ], "name": null, "output_values": [], "realizes": null, "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:feature_preprocessor" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.feature_preprocessing.FeaturePreprocessorChoice", "identifier": "50f56540-aa0f-4035-b015-5852856891e0", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "02d346ef-c031-44fa-b46c-7178f06073a0", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:densifier" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "Densifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees_preproc_for_classification" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesPreprocessorClassification" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees_preproc_for_regression" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesPreprocessorRegression" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:fast_ica" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "FastICA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:feature_agglomeration" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "FeatureAgglomeration" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:kernel_pca" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "KernelPCA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:kitchen_sinks" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomKitchenSinks" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:liblinear_svc_preprocessor" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibLinear_Preprocessor" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:no_preprocessing" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "NoPreprocessing" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:nystroem_sampler" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "Nystroem" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:pca" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PCA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:polynomial" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PolynomialFeatures" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:random_trees_embedding" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomTreesEmbedding" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_percentile_classification" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectPercentileClassification" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_percentile_regression" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectPercentileRegression" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:select_rates" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SelectRates" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:truncatedSVD" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "TruncatedSVD" } } ], "name": null, "output_values": [], "realizes": null, "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:classifier" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" }, "@type": "mls:Run", "executes": { "@type": "mls:Implementation", "_id": "_:autosklearn.pipeline.components.classification.ClassifierChoice", "identifier": "837c55bd-977d-4f59-9807-9c7a6cb55e7b", "implements": null, "name": null, "parameters": [], "version": null }, "identifier": "49f3bdc2-64f5-4772-8c6e-dae53758a91b", "input_values": [ { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:adaboost" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "AdaboostClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:bernoulli_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "BernoulliNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:decision_tree" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "DecisionTree" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:extra_trees" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "ExtraTreesClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:gaussian_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "GaussianNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:gradient_boosting" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "GradientBoostingClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:k_nearest_neighbors" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "KNearestNeighborsClassifier" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:lda" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LDA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:liblinear_svc" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibLinear_SVC" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:libsvm_svc" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "LibSVM_SVC" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:multinomial_nb" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "MultinomialNB" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:passive_aggressive" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "PassiveAggressive" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:qda" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "QDA" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:random_forest" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "RandomForest" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:sgd" }, "value": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@type": "mls:Algorithm", "_id": "SGD" } } ], "name": null, "output_values": [], "realizes": null, "version": null } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:balancing__strategy" }, "value": "none" } ] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:output_values" }, "value": [] }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@context" }, "value": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "executes": { "@context": { "@version": 1.1, "_id": "@id", "dcterms": "http://purl.org/dc/terms/", "implements": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "parameters": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:hasHyperParameter" }, "version": "dcterms:hasVersion" }, "@id": "mls:executes" }, "input_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasInput" }, "mls": "http://www.w3.org/ns/mls#", "name": "dcterms:title", "output_values": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#", "specified_by": "mls:specifiedBy", "value": "mls:hasValue", "xsd": "http://www.w3.org/2001/XMLSchema#" }, "@id": "mls:hasOutput" }, "realizes": { "@context": { "@version": 1.1, "_id": "@id", "mls": "http://www.w3.org/ns/mls#" }, "@id": "mls:implements" }, "version": "dcterms:hasVersion" } }, { "@type": "mls:HyperParameterSetting", "specified_by": { "@id": "_:@type" }, "value": "mls:Run" } ], "name": null, "output_values": [], "realizes": null, "version": null } ], "realizes": null, "version": null } ```

if it's too hard to confirm the json i can clean up what i have and check in so that it can be reviewed conceptually but (1) and (2) above basically explain what i did, and to me it is more efficient to hack certian bits until i know what i am actually trying to produce

vigsterkr commented 4 years ago

@chrisbarber i'll check into it asap in the meanwhile i'll just put together a json schema as that should be fairly easy to do and then that could be used to validate outputs in tests as well

chrisbarber commented 4 years ago

This could help clean up what I hacked together for (2) above, but not sure yet https://github.com/automl/auto-sklearn/issues/886#issuecomment-653423398