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112 lines
5.9 KiB
C
112 lines
5.9 KiB
C
/*****************************************************************************/
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/*IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. */
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/*By downloading, copying, installing or using the software you agree */
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/*to this license. If you do not agree to this license, do not download, */
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/*install, copy or use the software. */
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/* */
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/* */
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/*Copyright (c) 2005 Northwestern University */
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/*All rights reserved. */
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/*Redistribution of the software in source and binary forms, */
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/*with or without modification, is permitted provided that the */
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/*following conditions are met: */
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/* */
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/*1 Redistributions of source code must retain the above copyright */
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/* notice, this list of conditions and the following disclaimer. */
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/* */
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/*2 Redistributions in binary form must reproduce the above copyright */
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/* notice, this list of conditions and the following disclaimer in the */
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/* documentation and/or other materials provided with the distribution.*/
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/* */
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/*3 Neither the name of Northwestern University nor the names of its */
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/* contributors may be used to endorse or promote products derived */
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/* from this software without specific prior written permission. */
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/* */
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/*THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS */
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/*IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED */
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/*TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY, NON-INFRINGEMENT AND */
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/*FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL */
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/*NORTHWESTERN UNIVERSITY OR ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, */
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/*INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES */
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/*(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR */
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/*SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) */
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/*HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, */
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/*STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN */
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/*ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE */
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/*POSSIBILITY OF SUCH DAMAGE. */
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/******************************************************************************/
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/*************************************************************************/
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/** File: cluster.c **/
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/** Description: Takes as input a file, containing 1 data point per **/
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/** per line, and performs a fuzzy c-means clustering **/
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/** on the data. Fuzzy clustering is performed using **/
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/** min to max clusters and the clustering that gets **/
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/** the best score according to a compactness and **/
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/** separation criterion are returned. **/
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/** Author: Brendan McCane **/
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/** James Cook University of North Queensland. **/
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/** Australia. email: mccane@cs.jcu.edu.au **/
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/** **/
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/** Edited by: Jay Pisharath, Wei-keng Liao **/
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/** Northwestern University. **/
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/** **/
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/** ================================================================ **/
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/** **/
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/** Edited by: Sang-Ha Lee **/
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/** University of Virginia **/
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/** **/
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/** Description: No longer supports fuzzy c-means clustering; **/
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/** only regular k-means clustering. **/
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/** Simplified for main functionality: regular k-means **/
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/** clustering. **/
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/** **/
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/*************************************************************************/
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#include <stdio.h>
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#include <stdlib.h>
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#include <string.h>
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#include <limits.h>
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#include <math.h>
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#include <float.h>
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#include "kmeans.h"
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/*---< cluster() >-----------------------------------------------------------*/
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int cluster(int numObjects, /* number of input objects */
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int numAttributes, /* size of attribute of each object */
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float **attributes, /* [numObjects][numAttributes] */
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int num_nclusters,
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float threshold, /* in: */
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float ***cluster_centres /* out: [best_nclusters][numAttributes] */
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)
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{
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int nclusters;
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int *membership;
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float **tmp_cluster_centres;
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membership = (int *)malloc(numObjects * sizeof(int));
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nclusters = num_nclusters;
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srand(7);
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tmp_cluster_centres = kmeans_clustering(attributes,
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numAttributes,
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numObjects,
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nclusters,
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threshold,
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membership);
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if (*cluster_centres)
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{
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free((*cluster_centres)[0]);
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free(*cluster_centres);
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}
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*cluster_centres = tmp_cluster_centres;
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free(membership);
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return 0;
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}
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