Classes

Summary

class

class parent

truncated documentation

ARTimeSeriesRegressor

Base class to build a regressor on timeseries. The class computes one or several predictions at each time, between …

ApproximateNMFPredictor

Converts sklearn.decomposition.NMF into a predictor so that the prediction does not involve training even …

BaseEstimatorDebugInformation

Stores information when the outputs of a pipeline is computed. It as added by function @see fct alter_pipeline_for_debugging. …

BaseReciprocalTimeSeriesTransformer

Base for all timeseries preprocessing automatically applied within a predictor.

BaseReciprocalTransformer

Base for transform which transforms the features and the targets at the same time. It must also return another transform …

BaseTimeSeries

Base class to build a predictor on timeseries. The class computes one or several predictions at each time, between …

CategoriesToIntegers

Does something similar to what DictVectorizer

ClassifierAfterKMeans

Applies a k-means (see sklearn.cluster.KMeans) for each class, then adds the distance to each cluster …

CommonRegressorCriterion

Common class to implement various version of mean square error. …

ConstraintKMeans

Defines a constraint k-means. Clusters are modified to have an equal size. The algorithm is initialized …

CustomizedMultilayerPerceptron

Customized MLP Perceptron based on BaseMultilayerPerceptron. …

DecisionTreeLogisticRegression

Fits a logistic regression, then fits two other logistic regression for every observation on both sides of the border. …

DummyTimeSeriesRegressor

Dummy regressor for time series. Use past values as prediction.

ExtendedFeatures

Generates extended features such as polynomial features.

FeaturizerTypeError

Unable to process a type.

FunctionReciprocalTransformer

The transform is used to apply a function on a the target, predict, then transform the target back before scoring. …

IntervalRegressor

Trains multiple regressors to provide a confidence interval on prediction. It only works for single regression. …

KMeansL1L2

K-Means clustering with either norm L1 or L2. See notebook KMeans with norm L1 for an example.

LinearRegressorCriterion

Criterion which computes the mean square error assuming points falling into one node are approximated by a line …

MLCache

Implements a cache to reduce the number of trainings a grid search has to do.

NGramsMixin

Overloads method _word_ngrams

PermutationReciprocalTransformer

The transform is used to permute targets, predict, then permute the target back before scoring. nan values remain …

PiecewiseClassifier

Uses a decision tree to split the space of features into buckets and trains a logistic regression (default) …

PiecewiseEstimator

Uses a decision tree to split the space of features into buckets and trains a linear regression on each of them. …

PiecewiseRegressor

Uses a decision tree to split the space of features into buckets and trains a linear regression (default) on …

PiecewiseTreeRegressor

Implements a kind of piecewise linear regression by modifying the criterion used by the algorithm which builds a decision …

PipelineCache

Same as sklearn.pipeline.Pipeline but it can skip training if it detects a step was already trained the …

PredictableTSNE

t-SNE is an interesting transform which can only be used to study data as there is no way to reproduce the …

QuantileLinearRegression

Quantile Linear Regression or linear regression trained with norm L1. This class inherits from sklearn.linear_models.LinearRegression. …

QuantileMLPRegressor

Quantile MLP Regression or neural networks regression trained with norm L1. This class inherits from sklearn.neural_networks.MLPRegressor. …

SearchEnginePredictionImages

Extends class SearchEnginePredictions. Vectors are coming from images. The metadata must contains information …

SearchEnginePredictions

Extends class SearchEngineVectors by looking for neighbors to a vector X by looking neighbors to f(X)

SearchEngineVectors

Implements a kind of local search engine which looks for similar results assuming they are vectors. The class is …

SimpleRegressorCriterion

Implements mean square error criterion in a non efficient …

SimpleRegressorCriterionFast

Criterion which computes the mean square error assuming points falling into one node are approximated by a constant. …

SkBase

Pattern of a learner or a transform which follows the API of scikit-learn.

SkBaseClassifier

Defines a custom classifier.

SkBaseLearner

Pattern of a learner qui suit la même API que scikit-learn.

SkBaseRegressor

Defines a custom regressor.

SkBaseTransform

Pattern of a learner which follows the same API que scikit-learn.

SkBaseTransformLearner

A transform which hides a learner, it converts method predict into transform. This way, two learners can …

SkBaseTransformStacking

Un transform qui cache plusieurs learners, arrangés selon la méthode du stacking. …

SkException

custom exception

SkLearnParameters

Defines a class to store parameters of a learner or a transform.

TimeSeriesDifference

Computes timeseries differences.

TimeSeriesDifferenceInv

Computes the reverse of TimeSeriesDifference.

TimeSeriesRegressorMixin

Addition to sklearn.base.RegressorMixin.

TraceableCountVectorizer

Inherits from NGramsMixin which overloads method _word_ngrams

TraceableTfidfVectorizer

Inherits from NGramsMixin which overloads method _word_ngrams

TransferTransformer

Wraps a predictor or a transformer in a transformer. This model is frozen: it cannot be trained and only computes …

TransformedTargetClassifier2

Meta-estimator to classify on a transformed target. Useful for applying permutation transformation in classification …

TransformedTargetRegressor2

Meta-estimator to regress on a transformed target. Useful for applying a non-linear transformation in regression …

_DecisionTreeLogisticRegressionNode

Describes the tree structure hold by class DecisionTreeLogisticRegression. See also notebook Decision Tree and Logistic Regression. …