An Enhanced Feature Selection Algorithm Based on Maximum Relevance Minimum Redundancy and Splicing Strategy1
Author:
Affiliation:
1. Northeastern University,College of Information Science and Engineering,Shenyang,China
Funder
Research and Development
Major Research Plan
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10587298/10587321/10587389.pdf?arnumber=10587389
Reference15 articles.
1. A novel relation aware wrapper method for feature selection
2. Unsupervised feature selection algorithm based on redundancy learning and sparse regression
3. Feature selection in threes: Neighborhood relevancy, redundancy, and granularity interactivity
4. Exploiting fuzzy rough mutual information for feature selection
5. An Efficient Feature Selection and Classification Using Optimal Radial Basis Function Neural Network
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