mlpack
2.2.5

Performs the MST calculation using the DualTree Boruvka algorithm, using any type of tree. More...
Public Types  
typedef TreeType< MetricType, DTBStat, MatType >  Tree 
Convenience typedef. More...  
Public Member Functions  
DualTreeBoruvka (const MatType &dataset, const bool naive=false, const MetricType metric=MetricType())  
Create the tree from the given dataset. More...  
DualTreeBoruvka (Tree *tree, const MetricType metric=MetricType())  
Create the DualTreeBoruvka object with an already initialized tree. More...  
~DualTreeBoruvka ()  
Delete the tree, if it was created inside the object. More...  
void  ComputeMST (arma::mat &results) 
Iteratively find the nearest neighbor of each component until the MST is complete. More...  
Detailed Description
template<typenameMetricType=metric::EuclideanDistance,typenameMatType=arma::mat,template<typenameTreeMetricType,typenameTreeStatType,typenameTreeMatType>classTreeType=tree::KDTree>
class mlpack::emst::DualTreeBoruvka< MetricType, MatType, TreeType >
Performs the MST calculation using the DualTree Boruvka algorithm, using any type of tree.
For more information on the algorithm, see the following citation:
General usage of this class might be like this:
More advanced usage of the class can use different types of trees, pass in an alreadybuilt tree, or compute the MST using the O(n^2) naive algorithm.
 Template Parameters

MetricType The metric to use. MatType The type of data matrix to use. TreeType Type of tree to use. This should follow the TreeType policy API.
Member Typedef Documentation
◆ Tree
Constructor & Destructor Documentation
◆ DualTreeBoruvka() [1/2]
DualTreeBoruvka  (  const MatType &  dataset, 
const bool  naive = false , 

const MetricType  metric = MetricType() 

) 
Create the tree from the given dataset.
This copies the dataset to an internal copy, because treebuilding modifies the dataset.
 Parameters

data Dataset to build a tree for. naive Whether the computation should be done in O(n^2) naive mode. metric An optional instantiated metric to use.
◆ DualTreeBoruvka() [2/2]
DualTreeBoruvka  (  Tree *  tree, 
const MetricType  metric = MetricType() 

) 
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 treebuilding (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 Prebuilt tree. metric An optional instantiated metric to use.
◆ ~DualTreeBoruvka()
~DualTreeBoruvka  (  ) 
Delete the tree, if it was created inside the object.
Member Function Documentation
◆ ComputeMST()
void ComputeMST  (  arma::mat &  results  ) 
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.
The documentation for this class was generated from the following file:
 src/mlpack/methods/emst/dtb.hpp
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