0.Official website
https://www.oschina.net/p/mlpack?hmsr=aladdin1e1
1 Introduction
mlpack is a fast and flexible machine learning library (written in C++) whose purpose is to provide fast and convenient machine learning algorithms. mlpack provides these algorithms as simple command-line programs, Python bindings and C++ classes, and then they can be called in C++ code or Python to complete machine learning. It focuses on its scalability, high speed and ease of use. Its purpose is to allow new users to use machine learning through a simple and consistent API, while providing professional users with the high performance and maximum flexibility of C++. His performance exceeds a large number of similar machine learning libraries, such as WEKA, Shogun, MATLAB, mlpy and sklearn. mlpack contains a wealth of documents and tutorials, you can refer to the project homepage. The algorithms included in the tutorial are: NeighborSearch, RangeSearch, Linear Regression, The Euclidean Minimum Spanning Tree, K-Means, FastMKS (Fast max-kernel search) and so on.
mlpack provides a large number of classes or APIs for program calls, and also provides a lot of executable programs for users who do not understand C++. These executable files include: allkfn, allknn, emst, gmm, hmm_train, hmm_loglik, hmm_viterbi, hmm_generate, kernel_pca, kmeans, lars, linear_regression, local_coordinate_coding, mvu, nbc, nca, pca, radical, sparse_coding.
PS: When the blogger is finished, fill in the pits of opencv and matlab, I will open the pits of mlpack when I have time!