docs: add operations list

aimclub · Dec 6, 2023 · e8c8b2a · e8c8b2a
1 parent 9d9469f
commit e8c8b2a
Showing 1 changed file with 90 additions and 5 deletions.
diff --git a/docs/source/introduction/fedot_features/automation_features.rst b/docs/source/introduction/fedot_features/automation_features.rst
@@ -48,13 +48,13 @@ which uses scikit-learn's Recursive Feature Elimination (RFE).
    * - API name
      - Definition
    * - rfe_lin_reg
-     - RFE via Linear Regression regressor
+     - RFE via Linear Regression Regressor
    * - rfe_non_lin_reg
-     - RFE via Decision tree regressor
+     - RFE via Decision tree Regressor
    * - rfe_lin_class
-     - RFE via Logistic Regression classifier
+     - RFE via Logistic Regression Classifier
    * - rfe_non_lin_class
-     - RFE via Decision tree classifier
+     - RFE via Decision tree Classifier
 
 Feature extraction
 """"""""""""""""""
@@ -112,4 +112,89 @@ Apart from that there are other options whose names speak for themselves: ``'sta
 ``'automl'`` (the latter uses only AutoML models as pipeline nodes).
 
 .. note::
-    To make it simple, FEDOT uses ``auto`` by default to identify the best choice for you.
+    To make it simple, FEDOT uses ``auto`` by default to identify the best choice for you.
+
+
+Preprocessing operations
+^^^^^^^^^^^^^^^^^^^^^^^^
+
+.. csv-table:: Preprocessing operations
+   :header: 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,""
+
+
+Available operations
+^^^^^^^^^^^^^^^^^^^^
+
+.. csv-table:: Available operations
+   :header: 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,""