.. _l-classes:

Classes
=======

.. contents::
    :local:
    :depth: 1


Summary
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| class                                                                                                                            | class parent | truncated documentation                                                                                                                                                            |
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| :class:`ARTimeSeriesRegressor <mlinsights.timeseries.ar.ARTimeSeriesRegressor>`                                                  |              | Base class to build a regressor on timeseries. The class computes one or several predictions at each time, between ...                                                             |
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| :class:`ApproximateNMFPredictor <mlinsights.mlmodel.anmf_predictor.ApproximateNMFPredictor>`                                     |              | Converts :epkg:`sklearn:decomposition:NMF` into a predictor so that the prediction does not involve training even ...                                                              |
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| :class:`BaseEstimatorDebugInformation <mlinsights.helpers.pipeline.BaseEstimatorDebugInformation>`                               |              | Stores information when the outputs of a pipeline is computed. It as added by function @see fct alter_pipeline_for_debugging. ...                                                  |
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| :class:`BaseReciprocalTimeSeriesTransformer <mlinsights.timeseries.base.BaseReciprocalTimeSeriesTransformer>`                    |              | Base for all timeseries preprocessing automatically applied within a predictor.                                                                                                    |
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| :class:`BaseReciprocalTransformer <mlinsights.mlmodel.sklearn_transform_inv.BaseReciprocalTransformer>`                          |              | Base for transform which transforms the features and the targets at the same time. It must also return another transform ...                                                       |
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| :class:`BaseTimeSeries <mlinsights.timeseries.base.BaseTimeSeries>`                                                              |              | Base class to build a predictor on timeseries. The class computes one or several predictions at each time, between ...                                                             |
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| :class:`CategoriesToIntegers <mlinsights.mlmodel.categories_to_integers.CategoriesToIntegers>`                                   |              | Does something similar to what `DictVectorizer <http://scikit-learn.org/stable/modules/generated/sklearn.feature_extraction.DictVectorizer.html>`_ ...                             |
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| :class:`ClassifierAfterKMeans <mlinsights.mlmodel.classification_kmeans.ClassifierAfterKMeans>`                                  |              | Applies a *k-means* (see :epkg:`sklearn:cluster:KMeans`) for each class, then adds the distance to each cluster ...                                                                |
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| :class:`CommonRegressorCriterion <mlinsights.mlmodel._piecewise_tree_regression_common.CommonRegressorCriterion>`                |              | Common class to implement various version of `mean square error <https://en.wikipedia.org/wiki/Mean_squared_error>`_. ...                                                          |
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| :class:`ConstraintKMeans <mlinsights.mlmodel.kmeans_constraint.ConstraintKMeans>`                                                |              | Defines a constraint :epkg:`k-means`. Clusters are modified to have an equal size. The algorithm is initialized ...                                                                |
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| :class:`CustomizedMultilayerPerceptron <mlinsights.mlmodel.quantile_mlpregressor.CustomizedMultilayerPerceptron>`                |              | Customized MLP Perceptron based on `BaseMultilayerPerceptron <https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/neural_network/multilayer_perceptron.py#L40>`_. ... |
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| :class:`DecisionTreeLogisticRegression <mlinsights.mlmodel.decision_tree_logreg.DecisionTreeLogisticRegression>`                 |              | Fits a logistic regression, then fits two other logistic regression for every observation on both sides of the border. ...                                                         |
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| :class:`DummyTimeSeriesRegressor <mlinsights.timeseries.dummies.DummyTimeSeriesRegressor>`                                       |              | Dummy regressor for time series. Use past values as prediction.                                                                                                                    |
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| :class:`ExtendedFeatures <mlinsights.mlmodel.extended_features.ExtendedFeatures>`                                                |              | Generates extended features such as polynomial features.                                                                                                                           |
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| :class:`FeaturizerTypeError <mlinsights.mlmodel.ml_featurizer.FeaturizerTypeError>`                                              |              | Unable to process a type.                                                                                                                                                          |
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| :class:`FunctionReciprocalTransformer <mlinsights.mlmodel.sklearn_transform_inv_fct.FunctionReciprocalTransformer>`              |              | The transform is used to apply a function on a the target, predict, then transform the target back before scoring. ...                                                             |
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| :class:`IntervalRegressor <mlinsights.mlmodel.interval_regressor.IntervalRegressor>`                                             |              | Trains multiple regressors to provide a confidence interval on prediction. It only works for single regression. ...                                                                |
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| :class:`KMeansL1L2 <mlinsights.mlmodel.kmeans_l1.KMeansL1L2>`                                                                    |              | K-Means clustering with either norm L1 or L2. See notebook :ref:`kmeansl1rst` for an example.                                                                                      |
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| :class:`LinearRegressorCriterion <mlinsights.mlmodel.piecewise_tree_regression_criterion_linear.LinearRegressorCriterion>`       |              | Criterion which computes the mean square error assuming points falling into one node are approximated by a line ...                                                                |
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| :class:`MLCache <mlinsights.mlbatch.cache_model.MLCache>`                                                                        |              | Implements a cache to reduce the number of trainings a grid search has to do.                                                                                                      |
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| :class:`NGramsMixin <mlinsights.mlmodel.sklearn_text.NGramsMixin>`                                                               |              | Overloads method `_word_ngrams <https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/text.py#L148>`_ ...                                            |
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| :class:`PermutationReciprocalTransformer <mlinsights.mlmodel.sklearn_transform_inv_fct.PermutationReciprocalTransformer>`        |              | The transform is used to permute targets, predict, then permute the target back before scoring. nan values remain ...                                                              |
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| :class:`PiecewiseClassifier <mlinsights.mlmodel.piecewise_estimator.PiecewiseClassifier>`                                        |              | Uses a :epkg:`decision tree` to split the space of features into buckets and trains a logistic regression (default) ...                                                            |
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| :class:`PiecewiseEstimator <mlinsights.mlmodel.piecewise_estimator.PiecewiseEstimator>`                                          |              | Uses a :epkg:`decision tree` to split the space of features into buckets and trains a linear regression on each of them. ...                                                       |
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| :class:`PiecewiseRegressor <mlinsights.mlmodel.piecewise_estimator.PiecewiseRegressor>`                                          |              | Uses a :epkg:`decision tree` to split the space of features into buckets and trains a linear regression (default) on ...                                                           |
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| :class:`PiecewiseTreeRegressor <mlinsights.mlmodel.piecewise_tree_regression.PiecewiseTreeRegressor>`                            |              | Implements a kind of piecewise linear regression by modifying the criterion used by the algorithm which builds a decision ...                                                      |
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| :class:`PipelineCache <mlinsights.mlbatch.pipeline_cache.PipelineCache>`                                                         |              | Same as :epkg:`sklearn:pipeline:Pipeline` but it can skip training if it detects a step was already trained the ...                                                                |
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| :class:`PredictableTSNE <mlinsights.mlmodel.predictable_tsne.PredictableTSNE>`                                                   |              | :epkg:`t-SNE` is an interesting transform which can only be used to study data as there is no way to reproduce the ...                                                             |
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| :class:`QuantileLinearRegression <mlinsights.mlmodel.quantile_regression.QuantileLinearRegression>`                              |              | Quantile Linear Regression or linear regression trained with norm :epkg:`L1`. This class inherits from :epkg:`sklearn:linear_models:LinearRegression`. ...                         |
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| :class:`QuantileMLPRegressor <mlinsights.mlmodel.quantile_mlpregressor.QuantileMLPRegressor>`                                    |              | Quantile MLP Regression or neural networks regression trained with norm :epkg:`L1`. This class inherits from :epkg:`sklearn:neural_networks:MLPRegressor`. ...                     |
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| :class:`SearchEnginePredictionImages <mlinsights.search_rank.search_engine_predictions_images.SearchEnginePredictionImages>`     |              | Extends class :class:`SearchEnginePredictions`. Vectors are coming from images. The metadata must contains information ...                                                         |
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| :class:`SearchEnginePredictions <mlinsights.search_rank.search_engine_predictions.SearchEnginePredictions>`                      |              | Extends class :class:`SearchEngineVectors` by looking for neighbors to a vector *X* by looking neighbors to *f(X)* ...                                                             |
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| :class:`SearchEngineVectors <mlinsights.search_rank.search_engine_vectors.SearchEngineVectors>`                                  |              | Implements a kind of local search engine which looks for similar results assuming they are vectors. The class is ...                                                               |
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| :class:`SimpleRegressorCriterion <mlinsights.mlmodel.piecewise_tree_regression_criterion.SimpleRegressorCriterion>`              |              | Implements `mean square error <https://en.wikipedia.org/wiki/Mean_squared_error>`_ criterion in a non efficient ...                                                                |
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| :class:`SimpleRegressorCriterionFast <mlinsights.mlmodel.piecewise_tree_regression_criterion_fast.SimpleRegressorCriterionFast>` |              | Criterion which computes the mean square error assuming points falling into one node are approximated by a constant. ...                                                           |
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| :class:`SkBase <mlinsights.sklapi.sklearn_base.SkBase>`                                                                          |              | Pattern of a *learner* or a *transform* which follows the API of :epkg:`scikit-learn`.                                                                                             |
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| :class:`SkBaseClassifier <mlinsights.sklapi.sklearn_base_classifier.SkBaseClassifier>`                                           |              | Defines a custom classifier.                                                                                                                                                       |
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| :class:`SkBaseLearner <mlinsights.sklapi.sklearn_base_learner.SkBaseLearner>`                                                    |              | Pattern of a *learner* qui suit la même API que :epkg:`scikit-learn`.                                                                                                              |
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| :class:`SkBaseRegressor <mlinsights.sklapi.sklearn_base_regressor.SkBaseRegressor>`                                              |              | Defines a custom regressor.                                                                                                                                                        |
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| :class:`SkBaseTransform <mlinsights.sklapi.sklearn_base_transform.SkBaseTransform>`                                              |              | Pattern of a *learner* which follows the same API que :epkg:`scikit-learn`.                                                                                                        |
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| :class:`SkBaseTransformLearner <mlinsights.sklapi.sklearn_base_transform_learner.SkBaseTransformLearner>`                        |              | A *transform* which hides a *learner*, it converts method *predict* into *transform*. This way, two learners can ...                                                               |
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| :class:`SkBaseTransformStacking <mlinsights.sklapi.sklearn_base_transform_stacking.SkBaseTransformStacking>`                     |              | Un *transform* qui cache plusieurs *learners*, arrangés selon la méthode du `stacking <http://blog.kaggle.com/2016/12/27/a-kagglers-guide-to-model-stacking-in-practice/>`_. ...   |
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| :class:`SkException <mlinsights.sklapi.sklearn_parameters.SkException>`                                                          |              | custom exception                                                                                                                                                                   |
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| :class:`SkLearnParameters <mlinsights.sklapi.sklearn_parameters.SkLearnParameters>`                                              |              | Defines a class to store parameters of a *learner* or a *transform*.                                                                                                               |
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| :class:`TimeSeriesDifference <mlinsights.timeseries.preprocessing.TimeSeriesDifference>`                                         |              | Computes timeseries differences.                                                                                                                                                   |
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| :class:`TimeSeriesDifferenceInv <mlinsights.timeseries.preprocessing.TimeSeriesDifferenceInv>`                                   |              | Computes the reverse of :class:`TimeSeriesDifference`.                                                                                                                             |
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| :class:`TimeSeriesRegressorMixin <mlinsights.timeseries.base.TimeSeriesRegressorMixin>`                                          |              | Addition to :epkg:`sklearn:base:RegressorMixin`.                                                                                                                                   |
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| :class:`TraceableCountVectorizer <mlinsights.mlmodel.sklearn_text.TraceableCountVectorizer>`                                     |              | Inherits from :class:`NGramsMixin` which overloads method `_word_ngrams <https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/text.py#L148>`_ ...   |
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| :class:`TraceableTfidfVectorizer <mlinsights.mlmodel.sklearn_text.TraceableTfidfVectorizer>`                                     |              | Inherits from :class:`NGramsMixin` which overloads method `_word_ngrams <https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/feature_extraction/text.py#L148>`_ ...   |
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| :class:`TransferTransformer <mlinsights.mlmodel.transfer_transformer.TransferTransformer>`                                       |              | Wraps a predictor or a transformer in a transformer. This model is frozen: it cannot be trained and only computes ...                                                              |
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| :class:`TransformedTargetClassifier2 <mlinsights.mlmodel.target_predictors.TransformedTargetClassifier2>`                        |              | Meta-estimator to classify on a transformed target. Useful for applying permutation transformation in classification ...                                                           |
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| :class:`TransformedTargetRegressor2 <mlinsights.mlmodel.target_predictors.TransformedTargetRegressor2>`                          |              | Meta-estimator to regress on a transformed target. Useful for applying a non-linear transformation in regression ...                                                               |
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| :class:`_DecisionTreeLogisticRegressionNode <mlinsights.mlmodel.decision_tree_logreg._DecisionTreeLogisticRegressionNode>`       |              | Describes the tree structure hold by class :class:`DecisionTreeLogisticRegression`. See also notebook :ref:`decisiontreelogregrst`. ...                                            |
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