Abstract
The ever increasing growth of databases in the real time application is a major issue for the handling of large data. The data mining of the same is also a tedious task. The feature subset selection is a process for finding the irrelevant and redundant data and handling them. The proposed algorithm IFSSImproved Feature Subset Selection works in 2 major steps: 1. Find the irrelevant features and 2. Evaluate its fitness with Ant Colony Optimization (ACO). The Computation time taken to derive the results is taken to compare with different FSS algorithms.
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