Sk-learn API Family Introduction

Sk-learn API Family photo

Recently Sk-learn used more, will also be used often, will sk-learn all the contents of a bit, sorting ideas, and can be for future reference.

(HD images 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

Method process

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 algorithms

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