/usr/include/mlpack/methods/nystroem_method/kmeans_selection.hpp is in libmlpack-dev 1.0.10-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | /**
* @file kmeans_selection.hpp
* @author Marcus Edel
*
* Use the centroids of the K-Means clustering method for use in the Nystroem
* method of kernel matrix approximation.
*
* This file is part of MLPACK 1.0.10.
*
* MLPACK is free software: you can redistribute it and/or modify it under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation, either version 3 of the License, or (at your option) any
* later version.
*
* MLPACK is distributed in the hope that it will be useful, but WITHOUT ANY
* WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
* A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more
* details (LICENSE.txt).
*
* You should have received a copy of the GNU General Public License along with
* MLPACK. If not, see <http://www.gnu.org/licenses/>.
*/
#ifndef __MLPACK_METHODS_NYSTROEM_METHOD_KMEANS_SELECTION_HPP
#define __MLPACK_METHODS_NYSTROEM_METHOD_KMEANS_SELECTION_HPP
#include <mlpack/core.hpp>
#include <mlpack/methods/kmeans/kmeans.hpp>
namespace mlpack {
namespace kernel {
template<typename ClusteringType = kmeans::KMeans<> >
class KMeansSelection
{
public:
/**
* Use the K-Means clustering method to select the specified number of points
* in the dataset. You are responsible for deleting the returned matrix!
*
* @param data Dataset to sample from.
* @param m Number of points to select.
* @return Matrix pointer in which centroids are stored.
*/
const static arma::mat* Select(const arma::mat& data,
const size_t m,
const size_t maxIterations = 5)
{
arma::Col<size_t> assignments;
arma::mat* centroids = new arma::mat;
// Perform the K-Means clustering method.
ClusteringType kmeans(maxIterations);
kmeans.Cluster(data, m, assignments, *centroids);
return centroids;
}
};
}; // namespace kernel
}; // namespace mlpack
#endif
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