Module hummingbird.ml.operator_converters.sklearn

All scikit-learn operators converters are stored under this package.

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# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------

"""
All scikit-learn operators converters are stored under this package.
"""

Sub-modules

hummingbird.ml.operator_converters.sklearn.array_feature_extractor

Converters for scikit-learn feature selectors: SelectKBest, SelectPercentile, VarianceThreshold.

hummingbird.ml.operator_converters.sklearn.decision_tree

Converters for scikit-learn decision-tree-based models: DecisionTree, RandomForest and ExtraTrees.

hummingbird.ml.operator_converters.sklearn.decomposition

Converters for scikit-learn matrix decomposition transformers: PCA, KernelPCA, TruncatedSVD, FastICA.

hummingbird.ml.operator_converters.sklearn.discretizer

Converter for scikit-learn discretizers: Binarizer and KBinsDiscretizer.

hummingbird.ml.operator_converters.sklearn.gbdt

Converters for Sklearn's GradientBoosting models.

hummingbird.ml.operator_converters.sklearn.iforest

Converters for scikit-learn isolation forest.

hummingbird.ml.operator_converters.sklearn.imputer

Converter for scikit-learn Imputers: SimpleImputer and MissingIndicator

hummingbird.ml.operator_converters.sklearn.linear

Converters for scikit-learn linear models: LinearRegression, LogisticRegression, LinearSVC, SGDClassifier, LogisticRegressionCV.

hummingbird.ml.operator_converters.sklearn.mlp

Converters for scikit-learn MLP models: MLPClassifier, MLPRegressor

hummingbird.ml.operator_converters.sklearn.nb

Converters for scikit-learn Naive Bayes models: BernoulliNB, GaussianNB, MultinomialNB

hummingbird.ml.operator_converters.sklearn.normalizer

Converter for scikit-learn Normalizer.

hummingbird.ml.operator_converters.sklearn.one_hot_encoder

Converter for scikit-learn one hot encoder.

hummingbird.ml.operator_converters.sklearn.pipeline

Converters for operators necessary for supporting scikit-learn Pipelines.

hummingbird.ml.operator_converters.sklearn.poly_features

Converter for scikit-learn PolynomialFeatures.

hummingbird.ml.operator_converters.sklearn.scaler

Converters for scikit-learn scalers: RobustScaler, MaxAbsScaler, MinMaxScaler, StandardScaler.

hummingbird.ml.operator_converters.sklearn.sv

Converters for scikit-learn SV models: SVC, NuSVC. (LinearSVC is covered by linear_classifier.py).