Discrete feature weighting & selection algorithm

被引：0
|
作者：
Jankowski, N [1 ]
机构：
[1] Nicholas Copernicus Univ, Dept Informat, PL-87100 Torun, Poland
来源：
PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS 2003, VOLS 1-4 | 2003年
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A new method of feature weighting, useful also for feature selection has been described. It is quite efficient and gives quite accurate results. In general weighting algorithm may be used with any kind of learning algorithm. The weighting algorithm with k-nearest neighbors model was used to estimate the optimal feature base for a given distance measure. Results obtained with this algorithm clearly show its superior performance in several benchmark tests.
引用
收藏
页码：636 / 641
页数：6
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