mlpack::emst::DualTreeBoruvka< MetricType, TreeType > Class Template Reference
Performs the MST calculation using the Dual-Tree Boruvka algorithm, using any type of tree.
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List of all members.
Detailed Description
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
class mlpack::emst::DualTreeBoruvka< MetricType, TreeType >
Performs the MST calculation using the Dual-Tree Boruvka algorithm, using any type of tree.
For more information on the algorithm, see the following citation:
@inproceedings{
author = {March, W.B., Ram, P., and Gray, A.G.},
title = {{Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis,
Applications.}},
booktitle = {Proceedings of the 16th ACM SIGKDD International Conference
on Knowledge Discovery and Data Mining}
series = {KDD 2010},
year = {2010}
}
General usage of this class might be like this:
extern arma::mat data;
DualTreeBoruvka<> dtb(data);
arma::mat mstResults;
dtb.ComputeMST(mstResults);
More advanced usage of the class can use different types of trees, pass in an already-built tree, or compute the MST using the O(n^2) naive algorithm.
- Template Parameters:
-
| MetricType | The metric to use. IMPORTANT: this hasn't really been tested with anything other than the L2 metric, so user beware. Note that the tree type needs to compute bounds using the same metric as the type specified here. |
| TreeType | Type of tree to use. Should use DTBStat as a statistic. |
Definition at line 91 of file dtb.hpp.
Constructor & Destructor Documentation
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Create the tree from the given dataset.
This copies the dataset to an internal copy, because tree-building modifies the dataset.
- Parameters:
-
| data | Dataset to build a tree for. |
| naive | Whether the computation should be done in O(n^2) naive mode. |
| leafSize | The leaf size to be used during tree construction. |
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Create the DualTreeBoruvka object with an already initialized tree.
This will not copy the dataset, and can save a little processing power. Naive mode is not available as an option for this constructor; instead, to run naive computation, construct a tree with all the points in one leaf (i.e. leafSize = number of points).
- Note:
- Because tree-building (at least with BinarySpaceTree) modifies the ordering of a matrix, be sure you pass the modified matrix to this object! In addition, mapping the points of the matrix back to their original indices is not done when this constructor is used.
- Parameters:
-
| tree | Pre-built tree. |
| dataset | Dataset corresponding to the pre-built tree. |
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Delete the tree, if it was created inside the object.
Member Function Documentation
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Adds all the edges found in one iteration to the list of neighbors.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Adds a single edge to the edge list.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
The values stored in the tree must be reset on each iteration.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
This function resets the values in the nodes of the tree nearest neighbor distance, and checks for fully connected nodes.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Iteratively find the nearest neighbor of each component until the MST is complete.
The results will be a 3xN matrix (with N equal to the number of edges in the minimum spanning tree). The first row will contain the lesser index of the edge; the second row will contain the greater index of the edge; and the third row will contain the distance between the two edges.
- Parameters:
-
| results | Matrix which results will be stored in. |
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Unpermute the edge list and output it to results.
Member Data Documentation
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Connections.
Definition at line 111 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Reference to the data (this is what should be used for accessing data).
Definition at line 97 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Copy of the data (if necessary).
Definition at line 95 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Indicates whether or not O(n^2) naive mode will be used.
Definition at line 105 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
List of edge distances.
Definition at line 120 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
List of edge nodes.
Definition at line 116 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
List of edge nodes.
Definition at line 118 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Permutations of points during tree building.
Definition at line 114 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Indicates whether or not we "own" the tree.
Definition at line 102 of file dtb.hpp.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
For sorting the edge list after the computation.
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
template<typename MetricType = metric::EuclideanDistance, typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>>
Pointer to the root of the tree.
Definition at line 100 of file dtb.hpp.
The documentation for this class was generated from the following file: