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Title: GitHub - feiva/Statistical-Learning-Method_Code: 手写实现李航《统计学习方法》书中全部算法 · GitHub

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Description: 手写实现李航《统计学习方法》书中全部算法. Contribute to feiva/Statistical-Learning-Method_Code development by creating an account on GitHub.

Open Graph Description: 手写实现李航《统计学习方法》书中全部算法. Contribute to feiva/Statistical-Learning-Method_Code development by creating an account on GitHub.

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lvtengchao@pku.edu.cn

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	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#前言
	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/CodePic.png
传送门	http://www.pkudodo.com/
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#注其中mnist数据集已转换为csv格式由于体积为107m超过限制改为压缩包形式下载后务必先将mnist文件内压缩包直接解压
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#updates
Harold-Ran	https://github.com/Harold-Ran
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#实现
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#监督部分
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第二章-感知机
统计学习方法\|感知机原理剖析及实现	http://www.pkudodo.com/2018/11/18/1-4/
perceptron/perceptron_dichotomy.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/perceptron/perceptron_dichotomy.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第三章-k近邻
统计学习方法\|K近邻原理剖析及实现	http://www.pkudodo.com/2018/11/19/1-2/
KNN/KNN.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/KNN/KNN.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第四章-朴素贝叶斯
统计学习方法\|朴素贝叶斯原理剖析及实现	http://www.pkudodo.com/2018/11/21/1-3/
NaiveBayes/NaiveBayes.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/NaiveBayes/NaiveBayes.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第五章-决策树
统计学习方法\|决策树原理剖析及实现	http://www.pkudodo.com/2018/11/30/1-5/
DecisionTree/DecisionTree.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/DecisionTree/DecisionTree.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第六章-逻辑斯蒂回归与最大熵模型
统计学习方法\|逻辑斯蒂原理剖析及实现	http://www.pkudodo.com/2018/12/03/1-6/
统计学习方法\|最大熵原理剖析及实现	http://www.pkudodo.com/2018/12/05/1-7/
Logistic_and_maximum_entropy_models/logisticRegression.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/Logistic_and_maximum_entropy_models/logisticRegression.py
Logistic_and_maximum_entropy_models/maxEntropy.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/Logistic_and_maximum_entropy_models/maxEntropy.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第七章-支持向量机
统计学习方法\|支持向量机(SVM)原理剖析及实现	http://www.pkudodo.com/2018/12/16/1-8/
SVM/SVM.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/SVM/SVM.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第八章-提升方法
AdaBoost/AdaBoost.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/AdaBoost/AdaBoost.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第九章-em算法及其推广
EM/EM.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/EM/EM.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第十章-隐马尔可夫模型
HMM/HMM.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/HMM/HMM.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#无监督部分
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第十四章-聚类方法
K-means_Clustering.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/Clustering/K-means_Clustering/K-means_Clustering.py
Hierachical_Clustering.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/Clustering/Hierachical_Clustering/Hierachical_Clustering.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第十六章-主成分分析
PCA.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/PCA/PCA.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第十七章-潜在语意分析
LSA.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/LSA/LSA.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第十八章-概率潜在语意分析
PLSA.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/PLSA/PLSA.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第二十章-潜在狄利克雷分配
LDA.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/LDA/LDA.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#第二十一章-pagerank算法
Page_Rank.py	https://github.com/Dod-o/Statistical-Learning-Method_Code/blob/master/Page_Rank/Page_Rank.py
	https://github.com/feiva/Statistical-Learning-Method_Code/tree/master#许可--license
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)	https://creativecommons.org/licenses/by-nc-sa/4.0/
Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)	https://creativecommons.org/licenses/by-nc-sa/4.0/
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