I have regression Problem with 5 targest and need to perdict them simultaneously. is it possible to use mlens?
I have tried RF, xgboost as well as NN but the results are not good . size of my data 2800 samples.
I run the example in the tutorial but got the following error
``´ <<ImportError Traceback (most recent call last)
Cell In[101], line 1
----> 1 from mlens.ensemble import SuperLearner
2 from sklearn.linear_model import LogisticRegression
3 from sklearn.ensemble import RandomForestClassifier
File ~\anaconda3\Lib\site-packages\mlens\ensemble__init__.py:12
1 """ML-Ensemble
2
3 :author: Sebastian Flennerhag
(...)
9 can be used in conjunction with any other standard estimator.
10 """
---> 12 from .super_learner import SuperLearner
13 from .blend import BlendEnsemble
14 from .subsemble import Subsemble
File ~\anaconda3\Lib\site-packages\mlens\ensemble\super_learner.py:12
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
7 Super Learner class. Fully integrable with Scikit-learn.
8 """
10 from future import division
---> 12 from .base import BaseEnsemble
13 from ..index import FoldIndex, FullIndex
16 class SuperLearner(BaseEnsemble):
File ~\anaconda3\Lib\site-packages\mlens\ensemble\base.py:20
17 import warnings
19 from .. import config
---> 20 from ..parallel import Layer, ParallelProcessing, make_group
21 from ..parallel.base import BaseStacker
22 from ..externals.sklearn.validation import check_random_state
File ~\anaconda3\Lib\site-packages\mlens\parallel__init__.py:15
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
12 as handles for multiple instances and wrappers for standard parallel job calls.
13 """
14 from .backend import ParallelProcessing, ParallelEvaluation, Job, dump_array
---> 15 from .learner import Learner, EvalLearner, Transformer, EvalTransformer
16 from .layer import Layer
17 from .handles import Group, make_group, Pipeline
File ~\anaconda3\Lib\site-packages\mlens\parallel\learner.py:24
19 from ._base_functions import (
20 slice_array, set_output_columns, assign_predictions, score_predictions,
21 replace, save, load, prune_files, check_params)
22 from .base import OutputMixin, ProbaMixin, IndexMixin, BaseEstimator
---> 24 from ..metrics import Data
25 from ..utils import safe_print, print_time, format_name, assert_valid_pipeline
26 from ..utils.exceptions import (NotFittedError, FitFailedWarning,
27 ParallelProcessingError, NotInitializedError)
File ~\anaconda3\Lib\site-packages\mlens\metrics__init__.py:10
1 """ML-ENSEMBLE
2
3 :author: Sebastian Flennerhag
(...)
7 Metric utilities and functions.
8 """
---> 10 from ..externals.sklearn.scorer import make_scorer
11 from .metrics import rmse, mape, wape
12 from .utils import assemble_table, assemble_data, Data
File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\scorer.py:33
31 from .. import six
32 from .base import is_regressor
---> 33 from .type_of_target import type_of_target
36 class _BaseScorer(six.with_metaclass(ABCMeta, object)):
37 def init(self, score_func, sign, kwargs):
File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\type_of_target.py:10
6 # Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi
7 # License: BSD 3 clause
9 from future import division
---> 10 from collections import Sequence
13 from scipy.sparse import issparse
14 from scipy.sparse.base import spmatrix
ImportError: cannot import name 'Sequence' from 'collections'>>``
Hallo,
I have regression Problem with 5 targest and need to perdict them simultaneously. is it possible to use mlens? I have tried RF, xgboost as well as NN but the results are not good . size of my data 2800 samples.
I run the example in the tutorial but got the following error
``´ <<ImportError Traceback (most recent call last) Cell In[101], line 1 ----> 1 from mlens.ensemble import SuperLearner 2 from sklearn.linear_model import LogisticRegression 3 from sklearn.ensemble import RandomForestClassifier
File ~\anaconda3\Lib\site-packages\mlens\ensemble__init__.py:12 1 """ML-Ensemble 2 3 :author: Sebastian Flennerhag (...) 9 can be used in conjunction with any other standard estimator. 10 """ ---> 12 from .super_learner import SuperLearner 13 from .blend import BlendEnsemble 14 from .subsemble import Subsemble
File ~\anaconda3\Lib\site-packages\mlens\ensemble\super_learner.py:12 1 """ML-ENSEMBLE 2 3 :author: Sebastian Flennerhag (...) 7 Super Learner class. Fully integrable with Scikit-learn. 8 """ 10 from future import division ---> 12 from .base import BaseEnsemble 13 from ..index import FoldIndex, FullIndex 16 class SuperLearner(BaseEnsemble):
File ~\anaconda3\Lib\site-packages\mlens\ensemble\base.py:20 17 import warnings 19 from .. import config ---> 20 from ..parallel import Layer, ParallelProcessing, make_group 21 from ..parallel.base import BaseStacker 22 from ..externals.sklearn.validation import check_random_state
File ~\anaconda3\Lib\site-packages\mlens\parallel__init__.py:15 1 """ML-ENSEMBLE 2 3 :author: Sebastian Flennerhag (...) 12 as handles for multiple instances and wrappers for standard parallel job calls. 13 """ 14 from .backend import ParallelProcessing, ParallelEvaluation, Job, dump_array ---> 15 from .learner import Learner, EvalLearner, Transformer, EvalTransformer 16 from .layer import Layer 17 from .handles import Group, make_group, Pipeline
File ~\anaconda3\Lib\site-packages\mlens\parallel\learner.py:24 19 from ._base_functions import ( 20 slice_array, set_output_columns, assign_predictions, score_predictions, 21 replace, save, load, prune_files, check_params) 22 from .base import OutputMixin, ProbaMixin, IndexMixin, BaseEstimator ---> 24 from ..metrics import Data 25 from ..utils import safe_print, print_time, format_name, assert_valid_pipeline 26 from ..utils.exceptions import (NotFittedError, FitFailedWarning, 27 ParallelProcessingError, NotInitializedError)
File ~\anaconda3\Lib\site-packages\mlens\metrics__init__.py:10 1 """ML-ENSEMBLE 2 3 :author: Sebastian Flennerhag (...) 7 Metric utilities and functions. 8 """ ---> 10 from ..externals.sklearn.scorer import make_scorer 11 from .metrics import rmse, mape, wape 12 from .utils import assemble_table, assemble_data, Data
File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\scorer.py:33 31 from .. import six 32 from .base import is_regressor ---> 33 from .type_of_target import type_of_target 36 class _BaseScorer(six.with_metaclass(ABCMeta, object)): 37 def init(self, score_func, sign, kwargs):
File ~\anaconda3\Lib\site-packages\mlens\externals\sklearn\type_of_target.py:10 6 # Author: Arnaud Joly, Joel Nothman, Hamzeh Alsalhi 7 # License: BSD 3 clause 9 from future import division ---> 10 from collections import Sequence 13 from scipy.sparse import issparse 14 from scipy.sparse.base import spmatrix
ImportError: cannot import name 'Sequence' from 'collections'>>``