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basicmlalgs's Introduction

BasicMLAlgs

基础机器学习算法实现,以李航博士的《统计学习方法》为蓝本。

其他基础机器学习算法

《拓展》--1 主成分分析

MNIST_subset MATLAB代码:knn_matlab/knn.m

李航博士《统计学习方法》相关算法

《统计学习方法》第二章 感知器模型

例2.1 MATLAB代码:perceptron_matlab/perceptron.m
MNIST_subset MATLAB代码:perceptron_matlab/perceptron_mnist.m

《统计学习方法》第三章 K近邻法

MNIST_subset MATLAB代码:knn_matlab/knn.m

《统计学习方法》第四章 朴素贝叶斯

MNIST MATLAB代码:naiveBayes_matlab/naiveBayes.m

《统计学习方法》第五章 决策树

例5.2 MATLAB代码:decisionTree_matlab/decisionTree_exp5_2.m
例5.3 MATLAB代码:decisionTree_matlab/decisionTree_exp5_3.m
MNIST MATLAB代码:decisionTree_matlab/decisionTree.m

《统计学习方法》第六章 逻辑斯特回归

MNIST_subset MATLAB代码:logisticRegression_matlab/logisticRegression.m

《统计学习方法》第六章 最大熵模型

MNIST_subset MATLAB代码:maxEntropy_matlab/maxEntropy.m

《统计学习方法》第七章 支持向量机

例8.2 MATLAB代码:AdaBoost_matlab/AdaBoost_8_2.m

《统计学习方法》第八章 提升方法

例8.1 MATLAB代码:AdaBoost_matlab/AdaBoost_8_1.m
例8.2 MATLAB代码:AdaBoost_matlab/AdaBoost_8_2.m

《统计学习方法》第九章 最大期望EM及GMM

MATLAB代码:EM-GMM_matlab/GMM.m

《统计学习方法》第十章 隐马尔科夫模型

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