Classes

Summary

class

class parent

truncated documentation

BaseEstimatorDebugInformation

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

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. …

CustomizedMultilayerPerceptron

Customized MLP Perceptron based on BaseMultilayerPerceptron. …

ExtendedFeatures

Generates extended features such as polynomial features. Parameters ———- kind: string 'poly'

FeaturizerTypeError

Unable to process a type.

IntervalRegressor

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

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

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.

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 …