《MachineLearning，Tom Mitchell》
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mmc2015
北大信科学院，关注深度强化学习。http://net.pku.edu.cn/~maohangyu/
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《Machine Learning（Tom M. Mitchell）》读书笔记——4、第三章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bay原创 2014-11-15 09:20:47 · 2487 阅读 · 0 评论 -
《MachineLearning，Tom Mitchell》决策树的几点内容
几个概念：防止过分拟合的方法：几个注意事项：原创 2015-03-24 19:55:14 · 856 阅读 · 0 评论 -
Logistic Regression and Naive Bayes新的理解点
来自http://www.cs.cmu.edu/~tom/10701_sp11/Mitchell老师的公开课pptMAP相对于MLE而言，给出了待估计参数的先验概率；MLE仅仅根据训练集训练参数，而不考虑参数的先验概率：下面这张ppt说明了为什么要进行“regularization”以及regularization term的来源：原创 2015-04-07 10:58:39 · 1930 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——12、第十一章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-12-03 14:21:24 · 1476 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——9、第八章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-11-26 19:47:22 · 1172 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——6、第五章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bayes原创 2014-11-19 21:47:33 · 886 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——11、第十章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-12-01 21:49:58 · 1447 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——10、第九章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-11-27 21:09:10 · 1108 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——3、第二章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bayesian Le原创 2014-11-05 17:43:07 · 2366 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——5、第四章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bayes原创 2014-11-16 10:03:29 · 2536 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——14、第十三章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-12-07 20:41:52 · 957 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——1、全书结构
Product DetailsEditorial Reviews原创 2014-11-04 20:00:44 · 2375 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——2、第一章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bayesian Le原创 2014-11-04 20:11:44 · 2112 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——8、第七章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-11-25 20:17:07 · 1911 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——13、第十二章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6.原创 2014-12-03 20:51:09 · 2020 阅读 · 0 评论 -
《Machine Learning（Tom M. Mitchell）》读书笔记——7、第六章
1. Introduction (about machine learning)2. Concept Learning and the General-to-Specific Ordering3. Decision Tree Learning4. Artificial Neural Networks5. Evaluating Hypotheses6. Bayes原创 2014-11-24 18:33:26 · 3355 阅读 · 0 评论 -
降维：PCA
一直想总结一下降维的方法，借matchill老师的课，总结一下：PCA：PCA和ICA：降维方法：1、神经网络的隐含层2、LDA（线性判别分析）3、PCA4、ICA5、CCA6、信息增益（筛选特征）7、卡方检测原创 2015-04-26 16:54:23 · 1024 阅读 · 0 评论