Boosting is a META-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifier. icsiboost implements Adaboost over stumps (one-level decision trees) on discrete and continuous attributes (words and real values). See http://en.wikipedia.org/wiki/AdaBoost and the papers by Y. Freund and R. Schapire for more details [1]. This approach is one of most efficient and simple to combine continuous and nominal values. Our implementation is aimed at allowing training from millions of examples by hundreds of features in a reasonable time/memory.
标签： META-learning classifiers combining Boosting
上传时间： 2016-01-30
上传用户：songnanhua
AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.
标签： well-known algorithm AdaBoost Adaptive
上传时间： 2014-01-15
上传用户：qiaoyue
AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files
标签： well-known algorithm AdaBoost Adaptive
上传时间： 2013-12-31
上传用户：jiahao131
Learning Wireless Java
上传时间： 2014-11-23
上传用户：yxgi5
machine learning
上传时间： 2015-02-05
上传用户：来茴
Learning.Python.2nd.Edition
标签： Learning Edition Python nd
上传时间： 2014-11-24
上传用户：tfyt
Learning Standard C++ as a New Language
标签： Learning Language Standard New
上传时间： 2015-02-25
上传用户：libenshu01
USBFX2LK WDM drive for OSR s USB FX2 Learning Kit
标签： USBFX2LK Learning drive OSR
上传时间： 2015-03-11
上传用户：huannan88
Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning continuous non linear mappings For more than two or three in puts and for more than a few thousand dat apoints the computational expense of pre dictions is daunting We discuss drawbacks with previous approaches to dealing with this problem
标签： polynomial regression weighted instance
上传时间： 2013-11-28
上传用户：sunjet
Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP. Reference: X. Geng, D.-C. Zhan, and Z.-H. Zhou. Supervised nonlinear dimensionality reduction for visualization and classification. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2005, vol.35, no.6, pp.1098-1107.
标签： Description supervised algorithm S-ISOMAP
上传时间： 2015-04-10
上传用户：wfeel
