A Clustering-Guided Integer Brain Storm Optimizer for Feature Selection in High-Dimensional Data
For high-dimensional data with a large number of redundant features, existing feature selection algorithms still have the problem of “curse of dimensionality.” In view of this, the paper studies a new two-phase evolutionary feature selection algorithm, called clustering-guided integer brain storm op...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2021-01-01
|
Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2021/8462493 |