Positive Macroscopic Approximation for Fast Attribute Reduction
Attribute reduction is one of the challenging problems facing the effective application of computational intelligence technology for artificial intelligence. Its task is to eliminate dispensable attributes and search for a feature subset that possesses the same classification capacity as that of the...
Saved in:
Main Authors: | Zheng-Cai Lu, Zheng Qin, Qiao Jing, Lai-Xiang Shan |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2013-01-01
|
Series: | Journal of Applied Mathematics |
Online Access: | http://dx.doi.org/10.1155/2013/837281 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Approximate Accuracy Approaches to Attribute Reduction for Information Systems
by: Deshan Liu, et al.
Published: (2014-01-01) -
Fast Analytic Sampling Approximation from Cauchy Kernel
by: Youfa Li, et al.
Published: (2016-01-01) -
A Reinforcement Learning Based Traffic Control Strategy in a Macroscopic Fundamental Diagram Region
by: Lingyu Zheng, et al.
Published: (2022-01-01) -
Novel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction
by: Peng Yu, et al.
Published: (2025-01-01) -
A Variable Precision Attribute Reduction Approach in Multilabel Decision Tables
by: Hua Li, et al.
Published: (2014-01-01)