myazi / Mylearn
machine learning algorithm
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myLearn
make:生成可执行文件
demo.sh:调试入口
model.conf:模型参数
从线性到非线性模型
1、线性回归，岭回归，Lasso回归，局部加权线性回归
2、logistic回归，softmax回归，最大熵模型
3、广义线性模型
4、Fisher线性判别和线性感知机
5、三层神经网络
6、支持向量机
统计概率模型
1、高斯判别分析
2、朴素贝叶斯
3、隐马尔可夫模型
4、最大熵马尔科夫模型
5，条件随机场
6，马尔科夫决策过程
树模型
1、决策树 ID3，C4.5，CART
2、随机森林RF
3、Adaboost
4、GBDT
5、XGboost
6、孤立森林（异常检测）
聚类模型
1、层次聚类
2、原型聚类-K-means
3、模型聚类-GMM
4、EM算法-LDA主题模型
5、密度聚类-DBSCAN
6、图聚类-谱聚类
特征工程
1、特征工程
2、特征提取
3、特征选择
学习理论
1、基本概念
2、PAC理论
3、VC维
4、极大似然，最大后验概率，贝叶斯估计
5、模型选择与评价评价
6、模型诊断调参
深度学习 . .
哈希学习 . .
自然语言处理 . .
搜索推荐 . .
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