Feature selection by interactive clustering |
| |
Authors: | SK Wismath HP Soong SG Akl |
| |
Affiliation: | Department of Computing and Information Science, Queen's University, Kingston, Ontario, Canada |
| |
Abstract: | The results of experiments with a novel criterion for absolute non-parametric feature selection are reported. The basic idea of the new technique involves the use of computer graphics and the human pattern recognition ability to interactively choose a number of features, this number not being necessarily determined in advance, from a larger set of measurements. The triangulation method, recently proposed in the cluster analysis literature for mapping points from l-space to 2-space, is used to yield a simple and efficient algorithm for feature selection by interactive clustering. It is shown that a subset of features can thus be chosen which allows a significant reduction in storage and time while still keeping the probability of error in classification within reasonable bounds. |
| |
Keywords: | Feature selection Dimensionality reduction Interactive graphics Clustering Classifier design |
本文献已被 ScienceDirect 等数据库收录! |
|