Comparative Analysis of FCM and HCM Algorithm on Iris Data Set

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Clustering is a primary data description method in data mining which group's most similar data. The data clustering is an important problem in a wide variety of fields. Including data mining, pattern recognition, and bioinformatics. There are various algorithms used to solve this problem. This paper presents the comparison of the performance analysis of Fuzzy C Mean (FCM) clustering algorithm and compares it with Hard C Mean (HCM) algorithm on Iris flower data set. The authors measure time complexity and space complexity of FCM and HCM at Iris data set.

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