6.7 深度阅读材料

6.7.1 朴素贝叶斯

H. Zhang (2004). The optimality of Naive Bayes. Proc. FLAIRS. http://www.cs.unb.ca/~hzhang/publications/FLAIRS04ZhangH.pdf

J. Rennie et al. (2003), Tackling the poor assumptions of naive Bayes text classifiers, ICML.

Naive Bayes text classification http://nlp.stanford.edu/IR-book/html/htmledition/naive-bayes-text-classification-1.html

A. McCallum and K. Nigam (1998). A comparison of event models for Naive Bayes text classification. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.46.1529

V. Metsis, I. Androutsopoulos and G. Paliouras (2006). Spam filtering with Naive Bayes – Which Naive Bayes? http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.61.5542

6.7.2 K-最邻近

算法

“Multidimensional binary search trees used for associative searching”, Bentley, J.L., Communications of the ACM (1975) http://dl.acm.org/citation.cfm?doid=361002.361007

“Five balltree construction algorithms”, Omohundro, S.M., International Computer Science Institute Technical Report (1989) http://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.91.8209

6.7.3 支持向量机

《支持向量机导论》,[英] Nello Cristianini / John Shawe-Taylor 著

A Tutorial on Support Vector Regression http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.114.4288

Support-vector networks http://link.springer.com/article/10.1007%2FBF00994018

LIBSVM: A Library for Support Vector Machines http://www.csie.ntu.edu.tw/~cjlin/papers/libsvm.pdf

LIBLINEAR -- A Library for Large Linear Classification http://www.csie.ntu.edu.tw/~cjlin/liblinear/

Probability Estimates for Multi-class Classification by Pairwise Coupling http://www.csie.ntu.edu.tw/~cjlin/papers/svmprob/svmprob.pdf

6.7.4 决策树

L. Breiman, J. Friedman, R. Olshen, and C. Stone, “Classification and Regression Trees”, Wadsworth, Belmont, CA, 1984. http://www.stat.cmu.edu/~cshalizi/350/lectures/22/lecture-22.pdf

L. Breiman, and A. Cutler, “Random Forests” http://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm

6.7.5 神经网络

“Learning representations by back-propagating errors.” Rumelhart, David E., Geoffrey E. Hinton, and Ronald J. Williams. http://www.iro.umontreal.ca/~pift6266/A06/refs/backprop_old.pdf

“Backpropagation” Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen - Website, 2011. http://ufldl.stanford.edu/wiki/index.php/Backpropagation_Algorithm

“Stochastic Gradient Descent” L. Bottou - Website, 2010. http://leon.bottou.org/projects/sgd

Adam: A Method for Stochastic Optimization https://arxiv.org/abs/1412.6980

6.7.6 K-means

“k-means++: The advantages of careful seeding” David Arthur and Sergei Vassilvitskii http://ilpubs.stanford.edu:8090/778/1/2006-13.pdf

6.7.7 BIRCH

Tian Zhang, Raghu Ramakrishnan, Maron Livny BIRCH: An efficient data clustering method for large databases. http://www.cs.sfu.ca/CourseCentral/459/han/papers/zhang96.pdf

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