18种通过审核的候选算法 §分类 Classification 1. C4.5: Quinlan, J.R. 1993. C4.5: Programs for Machine Learning. Morgan 5 Kaufmann publishers inc 2. CART: L Breiman. J. Friedman. R. Olshen. and C. Stone. Classification and CAR T Regression Trees. Wadsworth, Belmont, CA, 1984 3. K Nearest Neighbours(kNN): Hastie, T. and Tibshirani, R. 1996. Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. KNN nte.(TPAM).18,6(Jun.1996),607-616 4. Naive Bayes Hand, D.J., Yu, K, 2001. ldiot's Bayes: Not So Stupid After All? nternat. Statist. Rev. 69. 385-398 Naive B §统计学习( Statistical Learning) 5. Vera o p York n,n1995. The Nature of Statistical Learning Theory. Springer- SVM 6.EM:McLachlan,G and Peel, D(2000). Finite Mixture Models. J. Wiley, New EM York §关联分析( Association Analysis) 7. Apriori: Rakesh Agrawal, Rama krishnan Srikant. Fast Algorithms for Mining non Association rules. In VLDb 94 8. FP-Tree: Han, J, Pei, J, and Yin, Y. 2000. Mining frequent patterns without candidate generation. In SIGMOD 00 FP-TreeC4.5 CART Naïve Bayes kNN SVM EM Apriori FP-Tree 18种通过审核的候选算法 §分类(Classification) 1. C4.5: Quinlan, J. R. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers Inc. 2. CART: L. Breiman, J. Friedman, R. Olshen, and C. Stone. Classification and Regression Trees. Wadsworth, Belmont, CA, 1984. 3. K Nearest Neighbours (kNN): Hastie, T. and Tibshirani, R. 1996. Discriminant Adaptive Nearest Neighbor Classification. IEEE Trans. Pattern Anal. Mach. Intell. (TPAMI). 18, 6 (Jun. 1996), 607-616. 4. Naive Bayes Hand, D.J., Yu, K., 2001. Idiot's Bayes: Not So Stupid After All? Internat. Statist. Rev. 69, 385-398. §统计学习(Statistical Learning) 5. SVM: Vapnik, V. N. 1995. The Nature of Statistical Learning Theory. Springer￾Verlag New York, Inc. 6. EM: McLachlan, G. and Peel, D. (2000). Finite Mixture Models. J. Wiley, New York. §关联分析(Association Analysis) 7. Apriori: Rakesh Agrawal,Ramakrishnan Srikant. Fast Algorithms for Mining Association Rules. In VLDB '94. 8. FP-Tree: Han, J., Pei, J., and Yin, Y. 2000. Mining frequent patterns without candidate generation. In SIGMOD '00