diff --git a/test/test-svm2.js b/test/test-svm2.js new file mode 100644 index 0000000..342624d --- /dev/null +++ b/test/test-svm2.js @@ -0,0 +1,28 @@ +var x = [[0, 0, 0], [0, 1, 1], [1, 1, 0], [2, 2, 2], [1, 2, 2], [2, 1, 2]]; +var y = ['A', 'A', 'B', 'B', 'C', 'C']; +var model = ml.learn({ + algorithm:ml.ML.SVM, + x:x, + y:y, + threshold:false, // no threshold function on output; highest value of svms is winner + labels:['A','B','C'], // multi-SVM + C : 15.0, // default : 1.0. C in SVM. + tol : 1e-5, // default : 1e-4. Higher tolerance --> Higher precision + max_passes : 200, // default : 20. Higher max_passes --> Higher precision + alpha_tol : 1e-5, // default : 1e-5. Higher alpha_tolerance --> Higher precision + + kernel : { type: 'rbf', sigma: 0.5 } // { type: "polynomial", c: 1, d: 5} +}); +print(toJSON(model).length+' Bytes') +print(model) +print(model.svms[0]) + +var test_data =[[0, 1.2, 0], + [2.1, 2, 3], + [2.1,1.1,2.0] +]; + +print(ml.classify(model,x)) +print(ml.classify(model,x.map(function (row) { return row.map(function (col) { return col+random(-0.3,0.3,0.001) })}))) +print(ml.classify(model,test_data)) +print(ml.stats.utils.best(ml.classify(model,[1,2,3])))