SK-Learn API Family Portrait Introduction

SK-Learn API Family Portrait

I have been using SK-Learn more recently and will use it frequently in the future. I have sorted out all the contents of Sk-Learn and organized my thoughts. , and available for future reference.

(HD pictures can be opened in a separate window with the right mouse button, or saved locally)

Basic public

base

sklearn.cluster

sklearn.datasets

Loaders

Samples generator

sklearn.exceptions

sklearn.pipeline

sklearn.utils

Methods

sklearn.cluster

classes

Functions

sklearn.cluster.bicluster

sklearn.model_selection

Splitter Classes

Splitter Functions

Hyper-parameter optimizers

Model validation

sklearn.dummy

sklearn.ensemble(Ensemble Methods)

sklearn.feature_extraction

sklearn.feature_selection

sklearn.gaussian_process

sklearn.metrics

Model Selection Interface

Classification metrics

Regression metrics

Multilabel ranking metrics

Clustering metrics

Biclustering metrics

Pairwise metrics

sklearn.multioutput(Multioutput regression and classification)

sklearn.calibration (Probability Calibration)

sklearn.cross_decomposition (Cross decomposition)

sklearn.preprocessing (Preprocessing and Normalization)

Mathematical algorithm

sklearn.covariance

sklearn.decomposition

sklearn.isotonic

sklearn.kernel_approximation

sklearn.kernel_ridge

sklearn.discriminant_analysis

sklearn.linear_model (Generalized Linear Models)

sklearn.manifold

sklearn.mixture( Gaussian Mixture Models )

sklearn.multiclass

sklearn.naive_bayes

sklearn.neighbors

sklearn.semi_supervised

sklearn.svm

sklearn.tree

NN algorithm

sklearn.neural_network

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