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python库之——sklearn

时间:2019-11-03 14:23:33      阅读:111      评论:0      收藏:0      [点我收藏+]

标签:https   UNC   rand   ESS   dataset   app   module   sele   ide   

机器学习库sklearn

官方documentation(资料)中分为不同的部分:

技术图片

 

其中我们主要讲User Guide(机器学习算法理论介绍)、API(程序实现方法):

一、User Guide

https://scikit-learn.org/stable/user_guide.html

模块 说明
Supervised learning监督学习 监督学习的各种算法介绍
Unsupervised learning非监督学习 非监督学习的各种算法介绍
Model selection and evaluation模型选择和评价
交叉验证、调参、模型评价、验证曲线
Inspection检查  
Dataset transformations数据转换 特征抽取、数据预处理、缺失值处理、非监督降维方法、随机投影、核近似、转换预测目标
Dataset loading utilities数据下载程序 玩具数据、真实数据集、生成数据、下载其它数据
Computing with scikit-learn利用sklearn计算 对大数据集的计算策略、计算表现、并行计算、资源管理和配置

二、api

和前面的内容对应,这个内容里给了在sklearn里的实现方法。

模块 功能

sklearn.base module: Base classes and utility functions
sklearn.calibration module: Probability Calibration(标准、标定)
sklearn.cluster: Clustering
sklearn.cluster.bicluster: Biclustering
sklearn.compose: Composite Estimators
sklearn.covariance: Covariance Estimators(协方差)
sklearn.cross_decomposition: Cross decomposition(交叉分解)
sklearn.datasets: Datasets
sklearn.decomposition: Matrix Decomposition
sklearn.discriminant_analysis: Discriminant Analysis(判别分析)
sklearn.dummy: Dummy estimators
sklearn.ensemble: Ensemble Methods
sklearn.exceptions module(exceptions模块): Exceptions and warnings
sklearn.experimental: Experimental
sklearn.feature_extraction: Feature Extraction
sklearn.feature_selection: Feature Selection
sklearn.gaussian_process: Gaussian Processes
sklearn.isotonic: Isotonic regression
sklearn.impute: Impute
sklearn.kernel_approximation Kernel Approximation
sklearn.kernel_ridge Kernel Ridge Regression
sklearn.linear_model: Generalized Linear Models?
sklearn.manifold: Manifold Learning
sklearn.metrics: Metrics
sklearn.mixture: Gaussian Mixture Models
sklearn.model_selection: Model Selection
sklearn.multiclass: Multiclass and multilabel classification
sklearn.multioutput: Multioutput regression and classification
sklearn.naive_bayes: Naive Bayes
sklearn.neighbors: Nearest Neighbors
sklearn.neural_network: Neural network models
sklearn.pipeline: Pipeline
sklearn.inspection: inspection
sklearn.preprocessing: Preprocessing and Normalization
sklearn.random_projection: Random projection?
sklearn.random_projection: Random projection?
sklearn.svm: Support Vector Machines?
sklearn.tree: Decision Trees?
sklearn.utils: Utilities(实用程序)

 

python库之——sklearn

标签:https   UNC   rand   ESS   dataset   app   module   sele   ide   

原文地址:https://www.cnblogs.com/ironan-liu/p/11785967.html

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