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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::linear_svm_C++\_documentation](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1svm_1_1LinearSVM.html)
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* [MLpack::linear_svm_Python_documentation](https://www.mlpack.org/doc/stable/python_documentation.html#linear_svm)
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* [**MLpack::linear_svm_C++\_documentation**](https://www.mlpack.org/doc/stable/doxygen/classmlpack_1_1svm_1_1LinearSVM.html)
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* [**MLpack::linear_svm_Python_documentation**](https://www.mlpack.org/doc/stable/python_documentation.html#linear_svm)
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added some of the links from the python documentation
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* [random_forest](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Classification/random_forest)
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* logistic_regression
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* [LinearSVM on Wikipedia](https://en.wikipedia.org/wiki/Support-vector_machine) |
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* [**random_forest**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Classification/random_forest)
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* [**logistic_regression**](https://gitlab.cs.uni-duesseldorf.de/stups/abschlussarbeiten/prolog-mlpack-libary/-/wikis/PrologMethods/Classification/logistic_regression)
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* [**LinearSVM on Wikipedia**](https://en.wikipedia.org/wiki/Support-vector_machine) |
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