基于最大margin決策樹(shù)歸納的研究ppt課件

1、基于最大margin決策樹(shù)歸納的研討 王海波符號(hào)學(xué)習(xí)研討組報(bào)告提綱國(guó)內(nèi)外研討現(xiàn)狀存在問(wèn)題研討目的與意義實(shí)現(xiàn)思緒進(jìn)一步的任務(wù)國(guó)內(nèi)外研討現(xiàn)狀之SVMSMO算法 Platt 1998聚類SVM Boley 2004Margin Tree Tibshirani 2007SVM的提出Vapnik 1995聚類SVM前往Margin Tree國(guó)內(nèi)外研討現(xiàn)狀之SVM反問(wèn)題SVM反問(wèn)題求解遺傳算法SVM反問(wèn)題求解K-means聚類SVM反問(wèn)題在決策樹(shù)中的運(yùn)用SVM反問(wèn)題的提出SVM反問(wèn)題在決策樹(shù)中的運(yùn)用基于最大margin的決策樹(shù)歸納求解SVM反問(wèn)題獲得具有最大margin的最優(yōu)超平面存在問(wèn)題時(shí)間復(fù)雜度SVM

2、反問(wèn)題的求解SMOSVM反問(wèn)題聚類處理SVM反問(wèn)題研討目的與意義目的：使SVM反問(wèn)題的求解在多項(xiàng)式時(shí)間內(nèi)完成，使決策樹(shù)的訓(xùn)練時(shí)間大大縮短。意義：由于訓(xùn)練過(guò)程的加快，使得基于Margin的決策樹(shù)歸納可以得到更廣泛的運(yùn)用實(shí)現(xiàn)思緒04.244.202.342.30聚類算法描畫(huà)及時(shí)間復(fù)雜度1 原始數(shù)據(jù)聚類：三類2 求margin矩陣：3(3-1)/2次SMO求解3 再次聚類得到margin tree4 求劃分超平面:一次SMO求解新算法時(shí)間復(fù)雜度：進(jìn)一步任務(wù)Margin tree 算法的實(shí)現(xiàn)及修正添加聚類的類別數(shù)遇到的問(wèn)題Margin 矩陣的求解修正SMO方法，使得不進(jìn)展數(shù)據(jù)處置也可得到margin找

3、一種方法，把數(shù)據(jù)變換后的margin復(fù)原回去參考文獻(xiàn)一V.N. Vapnik. The Nature of Statistical Learning Theory, Springer, New York, ISBN 0-387-98780-0,2000.Platt J C. Fast Training of SVM Using Sequential Minimal Optimization. In Scholkopf B, Burgs CJC, Smola A J eds. Advances In Kernel Methods-Support Vector Machine, Cambridge

4、, MA:MIT press, 1998, 185-208.Daniel Boley, Dongwei Cao. Training support vector machine using adaptive clusteringA. Proc. of Fourth SIAM International Conference on Data Mining C . Lake Buena Vista, FL, United States, 2004.Robert Tibshirani, Trevor Hastie. Margin trees for high-dimensional classifi

5、cation, Journal of Machine Learning Research Vol. 8, pp.637-652, 2007參考文獻(xiàn)二Volkan Vural, Jennifer G.Dy. A hierarchical method for multi-class support vector machines. International Conference on Machine Learning; Proceeding Series; Vol. 69, 2004.Xi-zhao Wang, Qiang He, De-Gang Chen, Daniel Yeung. A g

6、enetic algorithm for solving the inverse problem of support vector machines. Neuro computing 68(2005):225-238.Jie Zhu, Shu-fang Wu, Li Xue, Xi-zhao Wang. An improved algorithm for inverse problem of svms based on clustering. IEEE System, Man and Cybernetics Society, vol. 8, pp.4694-4698, 2006.Ning Li, Xi-zhao Wang, Li Xue. Decision tree induction based on large margin heuristic. IEEE System, Man and Cybernetics Society, vol. 8, pp.4699-4702, 2006.參考文獻(xiàn)三Platt, J., Cristianini, N., & Shawe-Taylor, J. (2000). Large margin da