Include dependency graph for dual_tree_kmeans_impl.hpp:
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Namespaces | |
| mlpack | |
| Linear algebra utility functions, generally performed on matrices or vectors. | |
| mlpack::kmeans | |
| K-Means clustering. | |
Functions | |
| template<typename TreeType , typename MatType > | |
| TreeType * | mlpack::kmeans::BuildTree (MatType &&dataset, std::vector< size_t > &oldFromNew, const typename std::enable_if< tree::TreeTraits< TreeType >::RearrangesDataset >::type *=0) |
| Call the tree constructor that does mapping. | |
| template<typename TreeType , typename MatType > | |
| TreeType * | mlpack::kmeans::BuildTree (MatType &&dataset, const std::vector< size_t > &, const typename std::enable_if< !tree::TreeTraits< TreeType >::RearrangesDataset >::type *=0) |
| Call the tree constructor that does not do mapping. | |
| template<typename TreeType > | |
| void | mlpack::kmeans::HideChild (TreeType &node, const size_t child, const typename std::enable_if_t< !tree::TreeTraits< TreeType >::BinaryTree > *junk=0) |
| Utility function for hiding children. More... | |
| template<typename TreeType > | |
| void | mlpack::kmeans::HideChild (TreeType &node, const size_t child, const typename std::enable_if_t< tree::TreeTraits< TreeType >::BinaryTree > *junk=0) |
| Utility function for hiding children. More... | |
| template<typename TreeType > | |
| void | mlpack::kmeans::RestoreChildren (TreeType &node, const typename std::enable_if_t< !tree::TreeTraits< TreeType >::BinaryTree > *) |
| Utility function for restoring children in a non-binary tree. | |
| template<typename TreeType > | |
| void | mlpack::kmeans::RestoreChildren (TreeType &node, const typename std::enable_if_t< tree::TreeTraits< TreeType >::BinaryTree > *junk=0) |
| Utility function for restoring children to a binary tree. More... | |
Detailed Description
An implementation of a Lloyd iteration which uses dual-tree nearest neighbor search as a black box. The conditions under which this will perform best are probably limited to the case where k is close to the number of points in the dataset, and the number of iterations of the k-means algorithm will be few.
mlpack is free software; you may redistribute it and/or modify it under the terms of the 3-clause BSD license. You should have received a copy of the 3-clause BSD license along with mlpack. If not, see http://www.opensource.org/licenses/BSD-3-Clause for more information.
