Feature selection using principal feature analysis

Abstract

Dimensionality reduction of a feature set is a common preprocessing step used for pattern recognition and classification applications. Principal Component Analysis (PCA) is one of the popular methods used, and can be shown to be optimal using different optimality criteria. However, it has the disadvantage that measurements from all the original features are… (More)
DOI: 10.1145/1291233.1291297

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