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zsglly木虫 (著名写手)
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[转帖]决策树资料
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近日来看了一些决策树的资料，在网上查找资料时，深感决策树的资料不是很多，特将本人能用上的一些资料共享在此。在此感谢数据挖掘研究院的论坛，里面有许多这方面的资料，只是没有整理在一起。 C5.0算法的Demo程序 http://www.rulequest.com/download.html http://www.rulequest.com/See5-demo.zip C5.0算法说明 See5: An Informal Tutorial http://www.rulequest.com/see5-win.html id3 和 c4.5代码公共包 http://218.22.25.142:8080/upload/92.zip 现在已经修改为 http://www.dmresearch.net/forum/upload/92.zip c5.0算法源代码 (c语言版) http://218.22.25.142:8080/upload/120.zip 决策树算法及应用拓展 http://218.22.25.142:8080/upload/204.zip http://www2.cs.uregina.ca/~hamilton/courses/831/index.html http://www2.cs.uregina.ca/~hamil ... rees/4_dtrees1.html 详细讲述C4.5算法的步骤 Build classification tree in Excel using C4.5 http://www.geocities.com/adotsaha/CTree/CtreeinExcel.html 决策树算法ID3和C4.5的提出者Ross Quinlan的个人网页 http://www.cse.unsw.edu.au/~quinlan/ Sample Applications Using See5/C5.0 Predicting Magnetic Properties of Crystals Profiling High Income Earners from Census Data Assessing Churn Risk Detecting Advertisements on the Web Identifying Spam Diagnosing Hypothyroidism Now Read On ... http://www.rulequest.com/see5-examples.html Free Decision Tree Software for Classification free and shareware: C4.5, the "classic" decision-tree tool, developed by J. R. Quinlan, (restricted distribution) http://www.cse.unsw.edu.au/~quinlan/ Classification Tree in Excel, from Angshuman Saha http://www.geocities.com/adotsaha/CTree/CtreeinExcel.html IND, provides Gini and C4.5 style decision trees and more. Publicly available from NASA but with export restrictions. http://ic.arc.nasa.gov/projects/bayes-group/ind/IND-program.html LMDT, builds Linear Machine Decision Trees (based on Brodley and Utgoff papers). http://mow.ecn.purdue.edu/~brodley/software/lmdt.html OC1, decision tree system continuous feature values; builds decision trees with linear combinations of attributes at each internal node; these trees then partition the space of examples with both oblique and axis-parallel hyperplanes. http://www.cs.jhu.edu/~salzberg/announce-oc1.html ODBCMINE, analyzes ODBC databases using C4.5, and outputs simple IF..ELSE decision rules in ascii. http://www.intsysr.com/odbcmine.htm PC4.5, a parallel version of C4.5 built with Persistent Linda (PLinda) system. http://www.cs.nyu.edu/~binli/pc4.5/ SMILES, advanced decision tree learner, with new splitting criteria, non-greedy search, extraction of different solutions, boosting, cost-sensitive learning, and more. http://www.dsic.upv.es/~flip/smiles/ Random forests from Leo Breiman, a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. http://www.stat.berkeley.edu/users/breiman ps: 不保证链接有效性，无效的话不要找我 [ Last edited by 幻影无痕 on 2006-11-25 at 07:36 ] |
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