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findcluster

Open clustering tool

Description

findcluster opens a UI to implement either fuzzy c-means or fuzzy subtractive clustering. For more information on:

example

findcluster(fileName) opens the UI, loads the data set in the file specified by fileName, and plots the first two dimensions of the data.

Examples

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Open the Clustering tool and load the data set in clusterdemo.dat.

findcluster('clusterDemo.dat')

You can configure the clustering options.

To cluster the data, click Start.

Input Arguments

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Data file name, specified as a string or character vector.

The data set file must have the extension .dat. Each line of the data set file contains one data point. For example, if you have 5-dimensional data with 100 data points, the file contains 100 lines, and each line contains five values.

Tips

  • Using the Clustering tool, you can obtain only the computed cluster centers. To obtain additional information for:

    • Fuzzy c-means clustering, such as the fuzzy partition matrix, cluster the data using fcm.

    • Subtractive clustering, such as the range of influence in each data dimension, cluster the data using subclust.

  • To use the same clustering data with either fcm or subclust, first load the data file into the MATLAB® workspace. For example, at the MATLAB command line, type:

    load clusterdemo.dat

Version History

Introduced before R2006a