Effective and efficient dimensionality reduction for large-scale and streaming data preprocessing

Abstract

Dimensionality reduction is an essential data preprocessing technique for large-scale and streaming data classification tasks. It can be used to improve both the efficiency and the effectiveness of classifiers. Traditional dimensionality reduction approaches fall into two categories: feature extraction and feature selection. Techniques in the feature… (More)
DOI: 10.1109/TKDE.2006.45

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