data_preprocessing
Configurable preprocessing pipeline and outlier clipping for sensor data.
The DataPreprocessor is an
sklearn-style Pipeline assembled from configurable DataTransformer
steps (see DataPreprocessor.STEP_REGISTRY).
The pipeline is configured via the train.data_preprocessor.steps config key.
- data_preprocessing.angle_transformer
- data_preprocessing.categorical_encoder
CategoricalEncoderCategoricalEncoder.categorical_featuresCategoricalEncoder.feature_names_out_CategoricalEncoder.numerical_columnsCategoricalEncoder.n_features_in_CategoricalEncoder.feature_names_in_CategoricalEncoder.one_hot_encoderCategoricalEncoder.categorical_columnsCategoricalEncoder.non_declared_categorical_featuresCategoricalEncoder.fit()CategoricalEncoder.get_feature_names_out()CategoricalEncoder.inverse_transform()CategoricalEncoder.transform()
- data_preprocessing.column_selector
- data_preprocessing.counter_diff_transformer
- data_preprocessing.data_clipper
- data_preprocessing.data_preprocessor
- data_preprocessing.duplicate_value_to_nan
- data_preprocessing.ffill_imputer
ForwardFillImputerForwardFillImputer.feature_names_in_ForwardFillImputer.feature_names_out_ForwardFillImputer.ffill_limit_ForwardFillImputer.categorical_featuresForwardFillImputer.numerical_columnsForwardFillImputer.categorical_columnsForwardFillImputer.non_declared_categorical_featuresForwardFillImputer.fit()ForwardFillImputer.get_feature_names_out()ForwardFillImputer.inverse_transform()ForwardFillImputer.transform()
- data_preprocessing.imputer
ImputerImputer.strategyImputer.categorical_featuresImputer.paramsImputer.numerical_imputerImputer.categorical_imputerImputer.n_features_in_Imputer.feature_names_in_Imputer.feature_names_out_Imputer.input_index_Imputer.numerical_columnsImputer.categorical_columnsImputer.non_declared_categorical_featuresImputer.fit()Imputer.get_feature_names_out()Imputer.inverse_transform()Imputer.transform()
- data_preprocessing.low_unique_value_filter
- data_preprocessing.scaler
- data_preprocessing.timestamp_transformer