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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::DrusillaSearch_C++\_documentation](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1DrusillaSelect.html)
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* [MLpack::QDAFN_C++\_documentation](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1QDAFN.html)
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* [MLpack::Approx_KFN_Python_documentation](https://www.mlpack.org/doc/stable/python_documentation.html#approx_kfn)
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* [**MLpack::DrusillaSearch_C++\_documentation**](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1DrusillaSelect.html)
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* [**MLpack::QDAFN_C++\_documentation**](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1neighbor_1_1QDAFN.html)
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* [**MLpack::Approx_KFN_Python_documentation**](https://www.mlpack.org/doc/stable/python_documentation.html#approx_kfn)
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added some of the links from the python documentation
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* [k-furthest-neighbor search](https://www.mlpack.org/doc/stable/kfn)
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* [k-nearest-neighbor search](https://www.mlpack.org/doc/stable/knn)
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* [Fast approximate furthest neighbors with data-dependent candidate selection (pdf)](http://ratml.org/pub/pdf/2016fast.pdf)
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* [Approximate furthest neighbor in high dimensions (pdf)](https://pdfs.semanticscholar.org/a4b5/7b9cbf37201fb1d9a56c0f4eefad04669c20.pdf) |
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* [**kfn**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Geometry/kfn)
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* [**knn**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Geometry/knn)
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* [**Fast approximate furthest neighbors with data-dependent candidate selection (pdf)**](http://ratml.org/pub/pdf/2016fast.pdf)
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* [**Approximate furthest neighbor in high dimensions (pdf)**](https://pdfs.semanticscholar.org/a4b5/7b9cbf37201fb1d9a56c0f4eefad04669c20.pdf) |
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