这里是《统计学习方法》的读书笔记，尝试自己实现里面的轮子。其实任何自己实现的轮子并不一定具备实际应用的能力，目的是通过代码来学习算法！:smile:
不全是自己写，参考均有说明！O(∩_∩)O

代码: https://github.com/acrafter/static_study/blob/master/perceptron.py

用kd树来查找k个近邻点
代码: https://github.com/acrafter/static_study/blob/master/knn/kd_tree.py

为什么叫朴素贝叶斯呢？
代码: https://github.com/acrafter/static_study/blob/master/Bayes.py

笔记: https://github.com/acrafter/static_study/blob/master/decision_tree/决策树.pdf
代码: https://github.com/acrafter/static_study/blob/master/decision_tree/decision_tree.py

笔记:
https://github.com/acrafter/static_study/blob/master/logistic_regression/浅析Logistic%20Regression.pdf 来源： https://chenrudan.github.io/blog/2016/01/09/logisticregression.html
https://github.com/acrafter/static_study/blob/master/logistic_regression/Logistic%20Regression 基础.pdf 来源： http://www.cnblogs.com/sparkwen/p/3441197.html
代码
https://github.com/acrafter/static_study/blob/master/logistic_regression/logistic_regression.py

笔记:
参考自vimsky.com
https://github.com/acrafter/static_study/blob/master/max_entropy/揭开机器学习的面纱：最大熵模型100行代码实现[Python版] - 纯净的天空.pdf
https://github.com/acrafter/static_study/blob/master/max_entropy/最大熵模型简介[例子+推导+GIS求解].pdf
代码：
https://github.com/acrafter/static_study/blob/master/max_entropy/max_ent.py

笔记：
https://github.com/acrafter/static_study/blob/master/support_vector_machine/支持向量机.pdf
代码：
https://github.com/acrafter/static_study/blob/master/support_vector_machine/smo.py

笔记：
https://github.com/acrafter/static_study/blob/master/adaboost/提升方法AdaBoost.pdf
代码：
https://github.com/acrafter/static_study/blob/master/adaboost/adaboost.py