Interactive Data Visualization of Fuzzy Membership Functions and Fuzzy Clustering

Since the volume of currently available data is growing from day to day, it is necessary to design and implement tools for a fast and comprehensive gain of knowledge from datasets created with this data. We can use the visualization of data as one of these methods - it is human and easy to understand. The presented paper aims to design and implement web application, which can be used for interactive visualization of data gained from fuzzification algorithms and fuzzy clustering. In this application, the user can interact with the visualization system and change form of input data, parameters, and visualization method.