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If you want a more detailed explanation, then go to the python documentation. There is most of the time a good explanation on how the methods work and what the parameters do.
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* [MLpack::knn_C++\_documentation](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1NeighborSearch.html)
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* [MLpack::knn_Python_documentation](https://www.mlpack.org/doc/stable/python_documentation.html#knn)
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* [**MLpack::knn_C++\_documentation**](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1NeighborSearch.html)
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* [**MLpack::knn_Python_documentation**](https://www.mlpack.org/doc/stable/python_documentation.html#knn)
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added some of the links from the python documentation
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* lsh
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* krann
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* kfn
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* [NeighborSearch tutorial (k-nearest-neighbors)](https://mlpack.org/doc/mlpack-git/doxygen/nstutorial.html)
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* [Tree-independent dual-tree algorithms (pdf)](http://proceedings.mlr.press/v28/curtin13.pdf) |
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* [**lsh**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Geometry/lsh)
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* [**kfn**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Geometry/kfn)
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* [**NeighborSearch tutorial (k-nearest-neighbors)**](https://mlpack.org/doc/mlpack-git/doxygen/nstutorial.html)
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* [**Tree-independent dual-tree algorithms (pdf)**](http://proceedings.mlr.press/v28/curtin13.pdf) |
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