Support Vector Machines in Javascript
⚠️ ⚠️ This is a simplified implementation of SVM, primarily meant for students to understand the algorithm. For real world applications, please check out libsvm-js ⚠️ ⚠️
Implementation of this simplified Sequential Minimization Optimization algorithm
npm install ml-svm
// Instantiate the svm classifier
var SVM = require('ml-svm');
var options = {
C: 0.01,
tol: 10e-4,
maxPasses: 10,
maxIterations: 10000,
kernel: 'rbf',
kernelOptions: {
sigma: 0.5
}
};
var svm = new SVM(options);
// Train the classifier - we give him an xor
var features = [[0,0],[0,1],[1,1],[1,0]];
var labels = [1, -1, 1, -1];
svm.train(features, labels);
// Let's see how narrow the margin is
var margins = svm.margin(features);
// Let's see if it is separable by testing on the training data
svm.predict(features); // [1, -1, 1, -1]
// I want to see what my support vectors are
var supportVectors = svm.supportVectors();
// Now we want to save the model for later use
var model = svm.toJSON();
/// ... later, you can make predictions without retraining the model
var importedSvm = SVM.load(model);
importedSvm.predict(features); // [1, -1, 1, -1]