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Title: GitHub - giaming/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 giaming/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 giaming/Statistical-Learning-Method_Code development by creating an account on GitHub.

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README	https://github.com/giaming/Statistical-Learning-Method_Code/tree/master
	https://github.com/giaming/Statistical-Learning-Method_Code/tree/master#前言
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传送门	http://www.pkudodo.com/
	https://github.com/giaming/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/giaming/Statistical-Learning-Method_Code/tree/master#另有意向为这个repo补充第二版无监督部分的大佬下拉到最下方联系我只要求注释完善即可我们可以成为好朋友一起冲鸭
	https://github.com/giaming/Statistical-Learning-Method_Code/tree/master#实现
	https://github.com/giaming/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/giaming/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/giaming/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/giaming/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/giaming/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/giaming/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/giaming/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/giaming/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/giaming/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/giaming/Statistical-Learning-Method_Code/tree/master#联系
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