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/*********************************************************************************
# Copyright (c) 2012, CyberPoint International, LLC
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
# * Redistributions of source code must retain the above copyright
# notice, this list of conditions and the following disclaimer.
# * Redistributions in binary form must reproduce the above copyright
# notice, this list of conditions and the following disclaimer in the
# documentation and/or other materials provided with the distribution.
# * Neither the name of the CyberPoint International, LLC nor the
# names of its contributors may be used to endorse or promote products
# derived from this software without specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL CYBERPOINT INTERNATIONAL, LLC BE LIABLE FOR ANY
# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
**********************************************************************************/
/*! \file KMeans.h
* \brief definitions for kmeans clustering algorithm
* \author Elizabeth Garbee
* \date Summer 2012
*/
#ifndef K_MEANS_H_
#define K_MEANS_H_
namespace gaussmix
{
/*! \brief kmeans cluster the given data
*
@param[in] dim dimensionality of data
@param[in] X pointer to n * dim array of data to be clustered
@param[in] n number of data points
@param[in] k desired number of clusters
@return heap-allocated k * dim array of cluster centroids (call must free) or 0 on error
*/
double * kmeans(int dim, double *X, int n, int k);
}
#endif /* K_MEANS_H_ */