Cyclic Shuffled Frog Leaping Algorithm Inspired Data Clustering

The era of internet has been filling our globe with tremendous high volume of data. These data have become the main raw material for various researches, business, etc. As the data volume is huge, categorizing the data will help in faster and quality data analysis. Clustering is one way of categorizing the data. As the digital data that is generated by any transaction is unpredictable, clustering can be the best option for categorizing it. Numerous clustering algorithms are at our disposal available. This paper focuses on adding modifications to the existing Shuffled Frog Leaping Algorithm and cluster the data. The proposed algorithm aims at enhancing the clustering, by taking the outliers into consideration and thereby improving the speed and quality of clusters formed.