JOURNAL ARTICLE

Linear feature extraction for multiclass problems

Abstract

Motivated by the need for a fast and effective feature extraction method for multiclass problems, a feature extraction method is developed to satisfy two requirements: (1) perform on a class-statistics basis (2) use discriminant information about covariance-difference as well as mean-difference. Experiments show that the new feature extraction method has fulfilled the requirements when the number of training samples is large. Experiments with a small number of training samples were also conducted for showing the limitation of feature extraction.

Keywords:
Feature extraction Pattern recognition (psychology) Feature (linguistics) Linear discriminant analysis Computer science Artificial intelligence Class (philosophy) Covariance Discriminant Mathematics Statistics

Metrics

10
Cited By
0.00
FWCI (Field Weighted Citation Impact)
8
Refs
0.28
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Face and Expression Recognition
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Imbalanced Data Classification Techniques
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Statistical Methods and Models
Physical Sciences →  Mathematics →  Statistics and Probability

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