Subset Selection in High Dimensional Data by Using Fast Clustring Technique

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Provided by: International Journal of Engineering Sciences & Research Technology (IJESRT)
Topic: Data Management
Format: PDF
A feature subset selection is an effective method for reducing dimensionality, removing irrelevant data, increasing learning accuracy and improving results comprehensibility. This process enhanced by cluster based FAST algorithm using MST construction. With the aim of choosing a subset of good features with respect to the target concepts, feature subset selection is an effective way for dropping dimensionality, remove irrelevant data, rising learning accuracy, and improving result comprehensibility. Features in different clusters are moderately independent.
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