Outlier Detection Using Hybrid Genetic Algorithm and Bacterial Foraging Optimization Algorithm
نویسندگان
چکیده
Data Mining is the process of extract useful information from the large data by using different mining techniques. Clustering and classification manage the large amount of data into different clusters according to their properties. Sometimes data arranged in clusters contain outliers that degrade the performance of the system. The outliers detected by K-Mean genetic algorithm also contain information; to detect this information and outlier’s properly K-Mean genetic bacterial foraging algorithm is applied. This paper also presents the comparison between K-Mean genetic algorithm and K-Mean genetic bacterial foraging algorithm.
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