Improved pseudoinverse linear discriminant analysis method for dimensionality reduction
Abstract
Pseudoinverse linear discriminant analysis (PLDA) is a classical method for solving small sample size problem. However, its performance is limited. In this paper, we propose an improved PLDA method which is faster and produces better classification accuracy when experimented on several datasets.Pseudoinverse linear discriminant analysis (PLDA) is a classical method for solving small sample size problem. However, its performance is limited. In this paper, we propose an improved PLDA method which is faster and produces better classification accuracy when experimented on several datasets.
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Journal Title
International Journal of Pattern Recognition and Artificial Intelligence
Volume
26
Issue
1
Subject
Cognitive and computational psychology