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aimclub / FEDOT

Automated modeling and machine learning framework FEDOT
https://fedot.readthedocs.io
BSD 3-Clause "New" or "Revised" License
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1035-docs #1222

Closed Lopa10ko closed 6 months ago

Lopa10ko commented 7 months ago

Add table of supported models and operations to the documentation. Also this list should be available in docstring of API parameter available_operations.

closes #1035

codecov[bot] commented 7 months ago

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Comparison is base (70d470a) 79.15% compared to head (1e91c0c) 79.45%. Report is 1 commits behind head on master.

Additional details and impacted files ```diff @@ Coverage Diff @@ ## master #1222 +/- ## ========================================== + Coverage 79.15% 79.45% +0.29% ========================================== Files 145 145 Lines 9937 9928 -9 ========================================== + Hits 7866 7888 +22 + Misses 2071 2040 -31 ```

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pep8speaks commented 6 months ago

Hello @Lopa10ko! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:

There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers:

Comment last updated at 2023-12-20 07:37:43 UTC
valer1435 commented 6 months ago

Думаю можно добавить в табличку информацию, в какой пресет какая операция попадает. А так очень полезная вещь - действительно был пробел в документации

kasyanovse commented 6 months ago

Думаю можно добавить в табличку информацию, в какой пресет какая операция попадает. А так очень полезная вещь - действительно был пробел в документации

@Lopa10ko Тогда надо будет еще добавить тест на проверку что все существующие пресеты упомянуты в таблицах.

Lopa10ko commented 6 months ago
Table of data processing operations API name|Model used|Definition|Problem|Tags ----------|-------------|------------|---------|---- `scaling`|`ScalingImplementation`|Scaling|Feature Scaling|['`fast_train`', ' `ts`', ' `*tree`'] `normalization`|`NormalizationImplementation`|Normalization|Feature Scaling|['`fast_train`', ' `ts`', ' `*tree`'] `simple_imputation`|`ImputationImplementation`|Imputation|Feature Imputation|['`fast_train`', ' `*tree`'] `pca`|`PCAImplementation`|Principal Component Analysis|Feature Reduction|['`fast_train`', ' `ts`', ' `*tree`'] `kernel_pca`|`KernelPCAImplementation`|Kernel Principal Component Analysis|Feature Reduction|['`ts`', ' `*tree`'] `fast_ica`|`FastICAImplementation`|Independent Component Analysis|Feature Reduction|['`ts`', ' `*tree`'] `poly_features`|`PolyFeaturesImplementation`|Polynomial Features|Feature Engineering|[''] `one_hot_encoding`|`OneHotEncodingImplementation`|Ohe-Hot Encoder|Feature Encoding|[''] `label_encoding`|`LabelEncodingImplementation`|Label Encoder|Feature Encoding|['`fast_train`', ' `*tree`'] `rfe_lin_reg`|`LinearRegFSImplementation`|Linear Regression Recursive Feature Elimination|Feature Selection|[''] `rfe_non_lin_reg`|`NonLinearRegFSImplementation`|Decision Tree Recursive Feature Elimination|Feature Selection|[''] `rfe_lin_class`|`LinearClassFSImplementation`|Logistic Regression Recursive Feature Elimination|Feature Selection|[''] `rfe_non_lin_class`|`NonLinearClassFSImplementation`|Decision Tree Recursive Feature Elimination|Feature Selection|[''] `isolation_forest_reg`|`IsolationForestRegImplementation`|Regression Isolation Forest|Feature Filtering|[''] `isolation_forest_class`|`IsolationForestClassImplementation`|Classification Isolation Forest|Feature Filtering|[''] `decompose`|`DecomposerRegImplementation`|Regression Decomposition|Decomposition|['`fast_train`', ' `ts`', ' `*tree`'] `class_decompose`|`DecomposerClassImplementation`|Classification Decomposition|Decomposition|['`fast_train`', ' `*tree`'] `resample`|`ResampleImplementation`|Resample features|Resampling|[''] `ransac_lin_reg`|`LinearRegRANSACImplementation`|Regression Random Sample Consensus|Feature Filtering|['`fast_train`', ' `*tree`'] `ransac_non_lin_reg`|`NonLinearRegRANSACImplementation`|DecisionTreeRegressor Random Sample Consensus|Feature Filtering|['`fast_train`', ' `*tree`'] `cntvect`|`sklearn.feature_extraction.text.CountVectorizer`|Count Vectorizer|Text Processing|[''] `text_clean`|`TextCleanImplementation`|Lemmatization and Stemming|Text Processing|[''] `tfidf`|`sklearn.feature_extraction.text.TfidfVectorizer`|TF-IDF Vectorizer|Text Processing|[''] `word2vec_pretrained`|`PretrainedEmbeddingsImplementation`|Word2Vec|Text Processing|[''] `lagged`|`LaggedTransformationImplementation`|Lagged Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `sparse_lagged`|`SparseLaggedTransformationImplementation`|Sparse Lagged Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `smoothing`|`TsSmoothingImplementation`|Smoothing Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `gaussian_filter`|`GaussianFilterImplementation`|Gaussian Filter Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `diff_filter`|`NumericalDerivativeFilterImplementation`|Derivative Filter Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `cut`|`CutImplementation`|Cut Tranformation|Timeseries Tranformation|['`fast_train`', ' `ts`'] `exog_ts`|`ExogDataTransformationImplementation`|Exogeneus Tranformation|Timeseries Tranformation|['']
Table of operations that are models API name|Model used|Definition|Problem|Tags ----------|-------------|------------|---------|---- `adareg`|`sklearn.ensemble.AdaBoostRegressor`|AdaBoost Regressor|Regression|['`fast_train`', ' `ts`', ' `*tree`'] `ar`|`AutoRegImplementation`|AutoRegression|Forecasting|['`fast_train`', ' `ts`'] `arima`|`ARIMAImplementation`|ARIMA|Forecasting|['`ts`'] `cgru`|`CGRUImplementation`|Convolutional Gated Recurrent Unit|Forecasting|['`ts`'] `bernb`|`sklearn.naive_bayes.BernoulliNB`|Naive Bayes Classifier (multivariate Bernoulli)|Classification|['`fast_train`'] `catboost`|`FedotCatBoostClassificationImplementation`|Catboost Classifier|Classification|['`*tree`'] `catboostreg`|`FedotCatBoostRegressionImplementation`|Catboost Regressor|Regression|['`*tree`'] `dt`|`sklearn.tree.DecisionTreeClassifier`|Decision Tree Classifier|Classification|['`fast_train`', ' `*tree`'] `dtreg`|`sklearn.tree.DecisionTreeRegressor`|Decision Tree Regressor|Regression|['`fast_train`', ' `ts`', ' `*tree`'] `gbr`|`sklearn.ensemble.GradientBoostingRegressor`|Gradient Boosting Regressor|Regression|['`*tree`'] `kmeans`|`sklearn.cluster.Kmeans`|K-Means clustering|Clustering|['`fast_train`'] `knn`|`FedotKnnClassImplementation`|K-nearest neighbors Classifier|Classification|['`fast_train`'] `knnreg`|`FedotKnnRegImplementation`|K-nearest neighbors Regressor|Regression|['`fast_train`', ' `ts`'] `lasso`|`sklearn.linear_model.Lasso`|Lasso Linear Regressor|Regression|['`fast_train`', ' `ts`'] `lda`|`LDAImplementation`|Linear Discriminant Analysis|Classification|['`fast_train`'] `lgbm`|`lightgbm.sklearn.LGBMClassifier`|Light Gradient Boosting Machine Classifier|Classification|[''] `lgbmreg`|`lightgbm.sklearn.LGBMRegressor`|Light Gradient Boosting Machine Regressor|Regression|['`*tree`'] `linear`|`sklearn.linear_model.LinearRegression`|Linear Regression Regressor|Regression|['`fast_train`', ' `ts`'] `logit`|`sklearn.linear_model.LogisticRegression`|Logistic Regression Classifier|Classification|['`fast_train`'] `mlp`|`sklearn.neural_network.MLPClassifier`|Multi-layer Perceptron Classifier|Classification|[''] `multinb`|`sklearn.naive_bayes.MultinomialNB`|Naive Bayes Classifier (multinomial)|Classification|['`fast_train`'] `qda`|`QDAImplementation`|Quadratic Discriminant Analysis|Classification|['`fast_train`'] `rf`|`sklearn.ensemble.RandomForestClassifier`|Random Forest Classifier|Classification|['`fast_train`', ' `*tree`'] `rfr`|`sklearn.ensemble.RandomForestRegressor`|Random Forest Regressor|Regression|['`fast_train`', ' `*tree`'] `ridge`|`sklearn.linear_model.Ridge`|Ridge Linear Regressor|Regression|['`fast_train`', ' `ts`'] `polyfit`|`PolyfitImplementation`|Polynomial fitter|Forecasting|['`fast_train`', ' `ts`'] `sgdr`|`sklearn.linear_model.SGDRegressor`|Stochastic Gradient Descent Regressor|Regression|['`fast_train`', ' `ts`'] `stl_arima`|`STLForecastARIMAImplementation`|STL Decomposition with ARIMA|Forecasting|['`ts`'] `glm`|`GLMImplementation`|Generalized Linear Models|Forecasting|['`fast_train`', ' `ts`'] `ets`|`ExpSmoothingImplementation`|Exponential Smoothing|Forecasting|['`fast_train`', ' `ts`'] `locf`|`RepeatLastValueImplementation`|Last Observation Carried Forward|Forecasting|['`fast_train`', ' `ts`'] `ts_naive_average`|`NaiveAverageForecastImplementation`|Naive Average|Forecasting|['`fast_train`', ' `ts`'] `svc`|`FedotSVCImplementation`|Support Vector Classifier|Classification|[''] `svr`|`sklearn.svm.LinearSVR`|Linear Support Vector Regressor|Regression|[''] `treg`|`sklearn.ensemble.ExtraTreesRegressor`|Extra Trees Regressor|Regression|['`*tree`'] `xgboost`|`xgboost.XGBClassifier`|Extreme Gradient Boosting Classifier|Classification|['`*tree`'] `xgbreg`|`xgboost.XGBRegressor`|Extreme Gradient Boosting Regressor|Regression|['`*tree`'] `cnn`|`FedotCNNImplementation`|Convolutional Neural Network|Classification|['']