Fuzzy Cluster - Java

Download the Cluster Java App.

Cluster

Control Section

Control

Load the Data File specified by the Input Section.

Cluster the Data using values from the Parameters Section.

View the resulting file as specified in the Output Section.

Graph the resulting file as specified in the Graph Section.

Exit the Program when you are done.

Input Section

Input

The working directory is where the program will try to read the input file and write the output file.

The Change buttons allow you to change the working directory and the data file.

The data file "butter.dat" is a text file that has each data item of N dimensions on a single row separated by white-space (spaces or tabs). So three dimensional data would have a row like:

2.0    3.4    128.0

When you load the data, the computer will try to figure out the number of data items, as well as the dimensionality of the data.

Output Section

Output

Indicate the number of clusters desired and that maximum iterations.

The default is a random seeding into the Clusters. It is possible to have a crisp initial partition file. Just uncheck "Random Initial Assignment" and you will be asked to select a partition file.

The partition file "book.par" is a text file that contains the placement of each data point for each cluster. If there are five data points then the first row of "book.par" would be the first clusters data points:

1 0 0 0 1

indicates Cluster One contains the first and last data point.

Parameters Section

Initial

Initial

All clustering algorithms need two basic parameters.

Fuzzy

Crisp clustering puts points in one cluster or another.

Fuzzy Clustering spreads points out over clusters.

Fuzzy

Fuzzy Clustering Pramaters

ISODATA

k-means uses a fixed number of clusters.

ISODATA Splits large clusters and Merges close clusters.

ISOData

ISODATA Parameters

 

Graph Section

Graph

Use the X and Y dropdowns to choose which dimensions of the data are mapped to X and Y.

Save will save the window as a PNG file.