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Meta-learning

Boosting is a Meta-learning approach that aims at combining an ensemble of weak classifiers to form

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.

標簽： Meta-learning classifiers combining Boosting

上傳時間： 2016-01-30

上傳用戶：songnanhua
AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yo

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.

標簽： well-known algorithm AdaBoost Adaptive

上傳時間： 2014-01-15

上傳用戶：qiaoyue
AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yo

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

標簽： well-known algorithm AdaBoost Adaptive

上傳時間： 2013-12-31

上傳用戶：jiahao131
Learning Wireless Java

Learning Wireless Java

標簽： Learning Wireless Java

上傳時間： 2014-11-23

上傳用戶：yxgi5
machine learning

machine learning

標簽： learning machine

上傳時間： 2015-02-05

上傳用戶：來茴
Learning.Python.2nd.Edition

Learning.Python.2nd.Edition

標簽： Learning Edition Python nd

上傳時間： 2014-11-24

上傳用戶：tfyt
Learning Standard C++ as a New Language

Learning Standard C++ as a New Language

標簽： Learning Language Standard New

上傳時間： 2015-02-25

上傳用戶：libenshu01
USBFX2LK WDM drive for OSR s USB FX2 Learning Kit

USBFX2LK WDM drive for OSR s USB FX2 Learning Kit

標簽： USBFX2LK Learning drive OSR

上傳時間： 2015-03-11

上傳用戶：huannan88
Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning c

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

標簽： polynomial regression weighted instance

上傳時間： 2013-11-28

上傳用戶：sunjet
Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.

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.

標簽： Description supervised algorithm S-ISOMAP

上傳時間： 2015-04-10

上傳用戶：wfeel

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Meta-learning

Boosting is a Meta-learning approach that aims at combining an ensemble of weak classifiers to form

AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yo

AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yo

Learning Wireless Java

machine learning

Learning.Python.2nd.Edition

Learning Standard C++ as a New Language

USBFX2LK WDM drive for OSR s USB FX2 Learning Kit

Locally weighted polynomial regression LWPR is a popular instance based al gorithm for learning c

Description: S-ISOMAP is a manifold learning algorithm, which is a supervised variant of ISOMAP.