MLPACK
1.0.4
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The NeighborSearch class is a template class for performing distance-based neighbor searches. More...
Public Member Functions | |
NeighborSearch (const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const bool naive=false, const bool singleMode=false, const size_t leafSize=20, const MetricType metric=MetricType()) | |
Initialize the NeighborSearch object, passing both a query and reference dataset. | |
NeighborSearch (const typename TreeType::Mat &referenceSet, const bool naive=false, const bool singleMode=false, const size_t leafSize=20, const MetricType metric=MetricType()) | |
Initialize the NeighborSearch object, passing only one dataset, which is used as both the query and the reference dataset. | |
NeighborSearch (TreeType *referenceTree, TreeType *queryTree, const typename TreeType::Mat &referenceSet, const typename TreeType::Mat &querySet, const bool singleMode=false, const MetricType metric=MetricType()) | |
Initialize the NeighborSearch object with the given datasets and pre-constructed trees. | |
NeighborSearch (TreeType *referenceTree, const typename TreeType::Mat &referenceSet, const bool singleMode=false, const MetricType metric=MetricType()) | |
Initialize the NeighborSearch object with the given reference dataset and pre-constructed tree. | |
~NeighborSearch () | |
Delete the NeighborSearch object. | |
void | Search (const size_t k, arma::Mat< size_t > &resultingNeighbors, arma::mat &distances) |
Compute the nearest neighbors and store the output in the given matrices. | |
Private Attributes | |
MetricType | metric |
Instantiation of kernel. | |
bool | naive |
Indicates if O(n^2) naive search is being used. | |
size_t | numberOfPrunes |
Total number of pruned nodes during the neighbor search. | |
std::vector< size_t > | oldFromNewQueries |
Permutations of query points during tree building. | |
std::vector< size_t > | oldFromNewReferences |
Permutations of reference points during tree building. | |
bool | ownQueryTree |
Indicates if we should free the query tree at deletion time. | |
bool | ownReferenceTree |
Indicates if we should free the reference tree at deletion time. | |
arma::mat | queryCopy |
Copy of query dataset (if we need it, because tree building modifies it). | |
const arma::mat & | querySet |
Query dataset (may not be given). | |
TreeType * | queryTree |
Pointer to the root of the query tree (might not exist). | |
arma::mat | referenceCopy |
Copy of reference dataset (if we need it, because tree building modifies it). | |
const arma::mat & | referenceSet |
Reference dataset. | |
TreeType * | referenceTree |
Pointer to the root of the reference tree. | |
bool | singleMode |
Indicates if single-tree search is being used (opposed to dual-tree). |
The NeighborSearch class is a template class for performing distance-based neighbor searches.
It takes a query dataset and a reference dataset (or just a reference dataset) and, for each point in the query dataset, finds the k neighbors in the reference dataset which have the 'best' distance according to a given sorting policy. A constructor is given which takes only a reference dataset, and if that constructor is used, the given reference dataset is also used as the query dataset.
The template parameters SortPolicy and Metric define the sort function used and the metric (distance function) used. More information on those classes can be found in the NearestNeighborSort class and the kernel::ExampleKernel class.
SortPolicy | The sort policy for distances; see NearestNeighborSort. |
MetricType | The metric to use for computation. |
TreeType | The tree type to use. |
Definition at line 104 of file neighbor_search.hpp.
mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::NeighborSearch | ( | const typename TreeType::Mat & | referenceSet, |
const typename TreeType::Mat & | querySet, | ||
const bool | naive = false , |
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const bool | singleMode = false , |
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const size_t | leafSize = 20 , |
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const MetricType | metric = MetricType() |
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) |
Initialize the NeighborSearch object, passing both a query and reference dataset.
Optionally, perform the computation in naive mode or single-tree mode, and set the leaf size used for tree-building. An initialized distance metric can be given, for cases where the metric has internal data (i.e. the distance::MahalanobisDistance class).
This method will copy the matrices to internal copies, which are rearranged during tree-building. You can avoid this extra copy by pre-constructing the trees and passing them using a diferent constructor.
referenceSet | Set of reference points. |
querySet | Set of query points. |
naive | If true, O(n^2) naive search will be used (as opposed to dual-tree search). This overrides singleMode (if it is set to true). |
singleMode | If true, single-tree search will be used (as opposed to dual-tree search). |
leafSize | Leaf size for tree construction (ignored if tree is given). |
metric | An optional instance of the MetricType class. |
mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::NeighborSearch | ( | const typename TreeType::Mat & | referenceSet, |
const bool | naive = false , |
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const bool | singleMode = false , |
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const size_t | leafSize = 20 , |
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const MetricType | metric = MetricType() |
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) |
Initialize the NeighborSearch object, passing only one dataset, which is used as both the query and the reference dataset.
Optionally, perform the computation in naive mode or single-tree mode, and set the leaf size used for tree-building. An initialized distance metric can be given, for cases where the metric has internal data (i.e. the distance::MahalanobisDistance class).
If naive mode is being used and a pre-built tree is given, it may not work: naive mode operates by building a one-node tree (the root node holds all the points). If that condition is not satisfied with the pre-built tree, then naive mode will not work.
referenceSet | Set of reference points. |
naive | If true, O(n^2) naive search will be used (as opposed to dual-tree search). This overrides singleMode (if it is set to true). |
singleMode | If true, single-tree search will be used (as opposed to dual-tree search). |
leafSize | Leaf size for tree construction (ignored if tree is given). |
metric | An optional instance of the MetricType class. |
mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::NeighborSearch | ( | TreeType * | referenceTree, |
TreeType * | queryTree, | ||
const typename TreeType::Mat & | referenceSet, | ||
const typename TreeType::Mat & | querySet, | ||
const bool | singleMode = false , |
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const MetricType | metric = MetricType() |
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) |
Initialize the NeighborSearch object with the given datasets and pre-constructed trees.
It is assumed that the points in referenceSet and querySet correspond to the points in referenceTree and queryTree, respectively. Optionally, choose to use single-tree mode. Naive mode is not available as an option for this constructor; instead, to run naive computation, construct a tree with all of the points in one leaf (i.e. leafSize = number of points). Additionally, an instantiated distance metric can be given, for cases where the distance metric holds data.
There is no copying of the data matrices in this constructor (because tree-building is not necessary), so this is the constructor to use when copies absolutely must be avoided.
referenceTree | Pre-built tree for reference points. |
queryTree | Pre-built tree for query points. |
referenceSet | Set of reference points corresponding to referenceTree. |
querySet | Set of query points corresponding to queryTree. |
singleMode | Whether single-tree computation should be used (as opposed to dual-tree computation). |
metric | Instantiated distance metric. |
mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::NeighborSearch | ( | TreeType * | referenceTree, |
const typename TreeType::Mat & | referenceSet, | ||
const bool | singleMode = false , |
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const MetricType | metric = MetricType() |
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) |
Initialize the NeighborSearch object with the given reference dataset and pre-constructed tree.
It is assumed that the points in referenceSet correspond to the points in referenceTree. Optionally, choose to use single-tree mode. 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). Additionally, an instantiated distance metric can be given, for the case where the distance metric holds data.
There is no copying of the data matrices in this constructor (because tree-building is not necessary), so this is the constructor to use when copies absolutely must be avoided.
referenceTree | Pre-built tree for reference points. |
referenceSet | Set of reference points corresponding to referenceTree. |
singleMode | Whether single-tree computation should be used (as opposed to dual-tree computation). |
metric | Instantiated distance metric. |
mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::~NeighborSearch | ( | ) |
Delete the NeighborSearch object.
The tree is the only member we are responsible for deleting. The others will take care of themselves.
void mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::Search | ( | const size_t | k, |
arma::Mat< size_t > & | resultingNeighbors, | ||
arma::mat & | distances | ||
) |
Compute the nearest neighbors and store the output in the given matrices.
The matrices will be set to the size of n columns by k rows, where n is the number of points in the query dataset and k is the number of neighbors being searched for.
k | Number of neighbors to search for. |
resultingNeighbors | Matrix storing lists of neighbors for each query point. |
distances | Matrix storing distances of neighbors for each query point. |
MetricType mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::metric [private] |
Instantiation of kernel.
Definition at line 280 of file neighbor_search.hpp.
bool mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::naive [private] |
Indicates if O(n^2) naive search is being used.
Definition at line 275 of file neighbor_search.hpp.
size_t mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::numberOfPrunes [private] |
Total number of pruned nodes during the neighbor search.
Definition at line 288 of file neighbor_search.hpp.
std::vector<size_t> mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::oldFromNewQueries [private] |
Permutations of query points during tree building.
Definition at line 285 of file neighbor_search.hpp.
std::vector<size_t> mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::oldFromNewReferences [private] |
Permutations of reference points during tree building.
Definition at line 283 of file neighbor_search.hpp.
bool mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::ownQueryTree [private] |
Indicates if we should free the query tree at deletion time.
Definition at line 272 of file neighbor_search.hpp.
bool mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::ownReferenceTree [private] |
Indicates if we should free the reference tree at deletion time.
Definition at line 270 of file neighbor_search.hpp.
arma::mat mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::queryCopy [private] |
Copy of query dataset (if we need it, because tree building modifies it).
Definition at line 257 of file neighbor_search.hpp.
const arma::mat& mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::querySet [private] |
Query dataset (may not be given).
Definition at line 262 of file neighbor_search.hpp.
TreeType* mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::queryTree [private] |
Pointer to the root of the query tree (might not exist).
Definition at line 267 of file neighbor_search.hpp.
arma::mat mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::referenceCopy [private] |
Copy of reference dataset (if we need it, because tree building modifies it).
Definition at line 255 of file neighbor_search.hpp.
const arma::mat& mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::referenceSet [private] |
Reference dataset.
Definition at line 260 of file neighbor_search.hpp.
TreeType* mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::referenceTree [private] |
Pointer to the root of the reference tree.
Definition at line 265 of file neighbor_search.hpp.
bool mlpack::neighbor::NeighborSearch< SortPolicy, MetricType, TreeType >::singleMode [private] |
Indicates if single-tree search is being used (opposed to dual-tree).
Definition at line 277 of file neighbor_search.hpp.