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ECML
2004
Springer
15 years 2 months ago
Improving Random Forests
Random forests are one of the most successful ensemble methods which exhibits performance on the level of boosting and support vector machines. The method is fast, robust to noise,...
Marko Robnik-Sikonja
NLPRS
2001
Springer
15 years 1 months ago
Ensembling based on Feature Space Restructuring with Application to WSD
We propose a new ensembling method of Support Vector Machines (SVMs) based on Feature Space Restructuring. In the proposed method, the weighted majority voting method is applied f...
Hiroya Takamura, Hiroyasu Yamada, Taku Kudo, Kaoru...
CJ
2004
90views more  CJ 2004»
14 years 9 months ago
Extended k-Nearest Neighbours based on Evidence Theory
An evidence theoretic classification method is proposed in this paper. In order to classify a pattern we consider its neighbours, which are taken as parts of a single source of ev...
Hui Wang, David A. Bell
HICSS
2003
IEEE
120views Biometrics» more  HICSS 2003»
15 years 2 months ago
A Primitive Study of Logrolling in e-Negotiation
e-Negotiation involves two or more agents multilaterally bargaining for mutual gain, using information technologies in a cooperative problem-solving (CPS) environment. This paper ...
Patrick C. K. Hung
AAAI
1996
14 years 10 months ago
Bagging, Boosting, and C4.5
Breiman's bagging and Freund and Schapire's boosting are recent methods for improving the predictive power of classi er learning systems. Both form a set of classi ers t...
J. Ross Quinlan