Dimension Reduction by Mutual Information Discriminant Analysis
نویسندگان
چکیده
منابع مشابه
Dimension Reduction by Mutual Information Discriminant Analysis
In the past few decades, researchers have proposed many discriminant analysis (DA) algorithms for the study of high-dimensional data in a variety of problems. Most DA algorithms for feature extraction are based on transformations that simultaneously maximize the between-class scatter and minimize the withinclass scatter matrices. This paper presents a novel DA algorithm for feature extraction u...
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During the past decades, to study high-dimensional data in a large variety of problems, researchers have proposed many Feature Extraction algorithms. One of the most effective approaches for optimal feature extraction is based on mutual information (MI). However it is not always easy to get an accurate estimation for high dimensional MI. In terms of MI, the optimal feature extraction is creatin...
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ژورنال
عنوان ژورنال: International Journal of Artificial Intelligence & Applications
سال: 2012
ISSN: 0976-2191
DOI: 10.5121/ijaia.2012.3303