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How to Use Fuzzy Clustering Software. Two types of clustering methods - Hard C means and Fuzzy C means. Limitation of software: -maximum number of data points: 150 -maximum number of dimensions: 10 -maximum number of clusters: 30. File Preparation for Fuzzy Clustering.
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How to Use Fuzzy Clustering Software • Two types of clustering methods - Hard C means and Fuzzy C means. • Limitation of software: -maximum number of data points: 150 -maximum number of dimensions: 10 -maximum number of clusters: 30
File Preparation for Fuzzy Clustering • Prepare a data file which consists of data points. For example, test1.txt file shown in the following window consists of 9 data points with 2 dimensions each.
Run the Fuzzy clustering software • Execute the fuzzycluster.exe file (double click the left button of the mouse), and then the following window will pop up.
Run the Fuzzy clustering software (cont.) • Input the data file name, number of data points, number of dimensions, number of clusters, type of C means, random number seed, etc. • The following is an example for the hard C mean:
Run the Fuzzy clustering software (cont.) • Then initial U matrix is shown and updated. Hit “return” key to continue the process until it is done.
Run the Fuzzy clustering software (cont.) • Then the final U matrix is shown. The C means of clusters and the classification of data points are also given.
Run the Fuzzy clustering software (cont.) • The following is the example for Fuzzy C means. It is similar to the hard C means but you need to input the m value.
Run the Fuzzy clustering software (cont.) • Fuzzy C means may take longer time to classify because the stopping criterion is the max improvement less than 0.0001.
Run the Fuzzy clustering software (cont.) • If the U values of a point are less than 0.5, then it cannot be classified, such as the data point 3 in the following example.