56 lines
2.2 KiB
Markdown
56 lines
2.2 KiB
Markdown
# Trees
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mlpack includes a number of space partitioning trees and other trees for its
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geometric techniques. These trees are built on [data matrices](../matrices.md)
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where each column in the matrix is a point in the tree. Trees are organized
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such that "nearby" points (with respect to a given distance metric) are
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generally grouped in the same node or branch of the tree.
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All trees in mlpack implement
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the [same API](../../developer/trees.md), allowing easy plug-and-play usage of
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different trees. The following tree types are available in mlpack:
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* [`KDTree`](trees/kdtree.md)
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* [`MeanSplitKDTree`](trees/mean_split_kdtree.md)
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* [`BallTree`](trees/ball_tree.md)
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* [`MeanSplitBallTree`](trees/mean_split_ball_tree.md)
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* [`RPTree`](trees/rp_tree.md)
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* [`MaxRPTree`](trees/max_rp_tree.md)
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* [`BinarySpaceTree`](trees/binary_space_tree.md)
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* [`UBTree`](trees/ub_tree.md)
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* [`CoverTree`](trees/cover_tree.md)
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* [`Octree`](trees/octree.md)
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* [`RTree`](trees/r_tree.md)
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* [`RStarTree`](trees/r_star_tree.md)
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* [`XTree`](trees/x_tree.md)
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* [`RPlusTree`](trees/r_plus_tree.md)
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* [`RPlusPlusTree`](trees/r_plus_plus_tree.md)
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* [`HilbertRTree`](trees/hilbert_r_tree.md)
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* [`RectangleTree`](trees/rectangle_tree.md)
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*Note:* this documentation is a work in progress. Not all trees are documented
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yet.
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---
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In general, it is not necessary to create an mlpack tree directly, but instead
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to simply specify the type of tree a particular algorithm should use via a
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template parameter. For instance, all of the algorithms below use mlpack trees
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and can have the type of tree specified via template parameters:
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<!-- TODO: document these! -->
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* [`NeighborSearch`](/src/mlpack/methods/neighbor_search/neighbor_search.hpp)
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(for k-nearest-neighbor and k-furthest-neighbor)
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* [`RangeSearch`](/src/mlpack/methods/range_search/range_search.hpp)
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* [`KDE`](/src/mlpack/methods/kde/kde.hpp)
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* [`FastMKS`](/src/mlpack/methods/fastmks/fastmks.hpp)
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* [`DTB`](/src/mlpack/methods/emst/dtb.hpp) (for computing Euclidean minimum
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spanning trees)
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* [`KRANN`](/src/mlpack/methods/rann/rann.hpp)
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---
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***Note:*** if you are looking for documentation on **decision trees**, see the
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documentation for the [`DecisionTree`](../methods/decision_tree.md) class.
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