Advancing Feature Selection Research

The rapid advance of computer based high-throughput technique has provided unparalleled opportunities for humans to expand capabilities in production, services, communications, and research. Meanwhile, immense quantities of high-dimensional data are accumulated challenging state-of-the-art data mining techniques. Feature selection is an essential step in successful data mining applications, which can effectively reduce data dimensionality by removing the irrelevant (and the redundant) features. In the past few decades, researchers have developed large amount of feature selection algorithms.

Provided by: Arizona State University Topic: Big Data Date Added: Jun 2010 Format: PDF

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