Fast Clustering Feature Selection Algorithm For high Dimensional Data (original) (raw)

A feature choice rule could also be evaluated from each the potency and effectiveness points of read .Feature choice involves distinctive a set of the foremost helpful options that produces compatible results because the original entire set of options. Whereas the potency considerations the time needed to search out a set of options, the effectiveness is said to the standard of the set of options. Based on these criteria, a quick clustering-based feature choice rule (FAST) is projected and through an experiment evaluated during this paper. The quick rule works in two steps. Within the start, options are divided into clusters by mistreatment graph-theoretic bunch ways. Within the second step, the foremost representative feature that's powerfully associated with target categories is chosen from every cluster to make a set of options. To make sure the potency of quick, we tend to adopt the economical minimum-spanning tree (MST) bunch techniques. Options in several clusters ar compa...

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