![]() ![]() For Ubuntu and Debian, mlpack’s dependencies can be installed through apt: sudo apt-get install libboost-all-dev libarmadillo-devĪfter the dependencies are successfully installed, you need to run following commands in terminal to install mlpack from source: wget First, you have to install Armadillo and Boost libraries. ![]() Here I explain how to install mlpack from source and also install its dependencies. ![]() Because in my case, Ubuntu, it installs an out-dated version of mlpack, which is 2.2.5 at the time of writing this. However, it’s not recommended to install mlpack using the package manager. Probably the easiest way to install mlpack is to use the package manager of your Linux distro (I personally use Ubuntu most often.). Besides, the installation of mlpack on Linux systems is fairly straightforward. This is not just my opinion but some other developers and researchers also agree on using Linux. Finally, I made a comparison between mlpack and scikit-learn with random forest classifier.įirst of all, I suggest you use a Linux distribution for machine learning projects. Then usage examples are given for both the CLI program and C++ API. First, I briefly explain how to install the mlpack on your system. I have also chosen the random forest classifier for the usage examples. In this post, I want to show usage examples which may help you use the mlpack library. No need to write a single line of C++ for using some algorithms. Comes with command-line programs that are ready to use.Its documentation is well written and has usage examples.mlpack has the following features, which I think it worth the try. mlpack is fast and scalable machine learning library for C++ (Based on its definition on its website.). Last year, I did a bit of research on the internet and found mlpack. Since I used C++ for my projects, I decided to try a C++ machine learning library. It’s good to have knowledge of other ML libraries in your arsenal. Because scikit-learn is a top quality ML package for Python and lets you use a machine learning algorithm in several lines of Python code, which is great!Īs a machine learning researcher, I personally like to try and use other machine learning libraries. Nowadays, most people use scikit-learn for machine learning projects. ![]()
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