Flexible Pavement

Deepali M. Nehare

Abstract


Real world data may contain hundreds of attributes in dataset many of which maybe irrelevant to the mining. Whenever we want to extract data from dataset that may beincomplete, inconsistent or contain noise because dataset collect and store data from various external sources. To overcome this problem clustering is mainly use to simplify the data, detecting the data patterns and identifying features of pattern. Feature selection in data mining is an effective way for reducing dimensionality, removing irrelevant data, increasing learning accuracy and improving result.


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