Variable Ranking for Online Ensemble Learning
Hassab Elgawi Osman
Image Science and Engineering Lab, Tokyo Institute of Technology, 4259 Nagatsuta, Midori-ku, Yokohama, Kanagawa 226-8503, Japan
In proposing, incremental feature selection based on correlation ranking (CR) for classification problems, we develop on-line training using the random forests (RF) algorithm, then evaluate the performance of the combination based on an NIPS 2003 Feature Selection Challenge dataset. Results show that our approach achieves performance comparable to others batch learning algorithms, including RF.
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