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Accurate classification of biological phenotypes is an essential task for medical decision making. The selection of subjects for classifier training and validation sets is a crucial step within this task. To evaluate the impact of two approaches for subject selection—randomization and clinical balancing, we applied six classification algorithms to a highly replicated publicly available breast cancer...
In this paper, Improved Particle Swarm Optimization (IPSO) approach is used in feature selection process - Linear Discriminant Analysis (LDA). This evolutionary random search method enhanced the classification rate with less computational time. The effectiveness of the proposed IPSO-LDA method is verified by employed Indian Face Database (IFD) and compare the results with existing methods.
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