Weighted Mutual Information for Feature Selection

Erik Schaffernicht; Horst–Michael Groß

doi:10.1007/978-3-642-21738-8_24

ScienceGate Book Chapters

BOOK-CHAPTER

Weighted Mutual Information for Feature Selection

Erik Schaffernicht Horst–Michael Groß

Year: 2011 Lecture notes in computer science Pages: 181-188 Publisher: Springer Science+Business Media

DOI: 10.1007/978-3-642-21738-8_24

Get Full-Text PDF Get Analytical Report

Keywords:

Mutual information Computer science Feature selection Artificial intelligence AdaBoost Selection (genetic algorithm) Pattern recognition (psychology) Feature (linguistics) Data mining Machine learning Support vector machine

Metrics

Cited By

1.13

FWCI (Field Weighted Citation Impact)

Refs

0.77

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Face and Expression Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Metaheuristic Optimization Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Weighted Mutual Information for Feature Selection

Metrics

Citation History

Topics

Related Documents

Feature selection based on weighted conditional mutual information

Structural feature selection via weighted sparse regression with mutual information

Feature Selection Method Based on Weighted Mutual Information for Imbalanced Data

Weighted Average Pointwise Mutual Information for Feature Selection in Text Categorization

Quadratic Mutual Information Feature Selection