Comparison of Clustering Algorithms Using KNIME Tool

Development of present-day methods for logical information gathering has brought about substantial scale collection of information relating to different fields. Web mining is an exceptionally hot research area which joins two of the actuated research topics DM and WWW. The most perceived approach is to classify Web mining into Web content mining, Web structure mining, and Web usage mining. Clustering is appropriate part of Web mining. Clustering is a task to mine information, and a typical strategy to measure information which is utilized as a part of various fields, including ML, design acknowledgment, photograph investigation, data recovery, and bioinformatics. In this paper, the comparison of different clustering techniques using KNIME tool is implemented. The algorithms analyzed are: K-means and FCM on different types of dataset.