@Test public void classification() throws IOException { Table moneyball = Table.read().csv("../data/baseball.csv"); RandomForest playoffsModel = new RandomForest(moneyball.smile().nominalDataset("Playoffs", "RS", "RA", "OBP"), 1); assertNotNull(playoffsModel.toString()); }
@Override public RandomForest train(double[][] x, int[] y) { return new RandomForest(attributes, x, y, ntrees, maxNodes, nodeSize, mtry, subsample, rule, null); } }
private RandomForest(int nTrees, int[] classArray, NumericColumn... columns) { double[][] data = DoubleArrays.to2dArray(columns); this.classifierModel = new smile.classification.RandomForest(data, classArray, nTrees); }
private static SoftClassifier<double[]> trainModel(String learner, double[][] x, int[] y) { if (learner.equals("SVM")) { SVM<double[]> svm = new SVM<>(new LinearKernel(), 0.01); svm.learn(x, y); svm.finish(); svm.trainPlattScaling(x, y); return svm; } else if (learner.equals("RandomForest")) { RandomForest randomForest = new RandomForest(x, y, 100); return randomForest; } else { throw new IllegalArgumentException("Unknow learning algorithm: " + learner); } }