This sandbox for training SVM algorithms to classify a set of 2 dimensional data points is a part of my introduction to machine learning in our "Computational Neuroscience Student Initiative". It offers a canvas that visualizes the data as well as the guessed decisions of your trained SVM algorithm.
You are a medical researcher and you and your team developed a new vaccine against a dangerous virus. Hower this vaccine sadly does not work on every patient. You gathered the age and doses for each test patient you vaccinated and note the vaccination result after a few weeks. So you know for about 1000 patients their age, the doses which they were vaccinated with and whether or not the vaccination was successful.
It's your task to implement the decision function, the hyperplane function, kernel function, the function to find the hyperparameters and the cross validation algorithm. You can ignore all files except for the ML.java file, which already contains all methods, some configuration variables and instructions on what to do.
All you need is Java setup on your machine and an IDE. There are no additional libraries, that need to be installed.