findcluster

Open clustering tool

Description

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

example

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

Examples

Open Clustering Tool and Load Data Set

findcluster('clusterdemo.dat')

Input Arguments

collapse all

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

Introduced before R2006a