### Question:
RandomForestClassifier extends AbstractTextEnabledNumericClassifier { @Override public int predict(double[] data) { if (randomForest == null) throw new RuntimeException("NumericClassifier has to be fitted first"); return randomForest.predict(data); } RandomForestClassifier(int nTrees); @Override void fit(double[][] data, int[] labels); @Override int[] predictMultiple(double[][] data); @Override int predict(double[] data);  }### Answer:
@Disabled @Test public void testRandomForestWeatherData() throws Exception { ArffParser arffParser = new ArffParser(); arffParser.setResponseIndex(4); AttributeDataset weather = arffParser.parse(ClassLoader.getSystemClassLoader().getResourceAsStream("weather.nominal.arff")); double[][] x = weather.toArray(new double[weather.size()][]); int[] y = weather.toArray(new int[weather.size()]); int n = x.length; LOOCV loocv = new LOOCV(n); int error = 0; for (int i = 0; i < n; i++) { double[][] trainx = Math.slice(x, loocv.train[i]); int[] trainy = Math.slice(y, loocv.train[i]); RandomForest forest = new RandomForest(weather.attributes(), trainx, trainy, 100); if (y[loocv.test[i]] != forest.predict(x[loocv.test[i]])) error++; } assertTrue(error <= 7); }
@Disabled @Test public void testRandomForestUSPSNominal() throws Exception { DelimitedTextParser parser = new DelimitedTextParser(); parser.setResponseIndex(new NominalAttribute("class"), 0); AttributeDataset train = parser.parse("USPS Train", ClassLoader.getSystemClassLoader().getResourceAsStream("zip.train")); AttributeDataset test = parser.parse("USPS Test", ClassLoader.getSystemClassLoader().getResourceAsStream("zip.test")); double[][] x = train.toArray(new double[train.size()][]); int[] y = train.toArray(new int[train.size()]); double[][] testx = test.toArray(new double[test.size()][]); int[] testy = test.toArray(new int[test.size()]); for (double[] xi : x) { for (int i = 0; i < xi.length; i++) { xi[i] = java.lang.Math.round(255 * (xi[i] + 1) / 2); } } for (double[] xi : testx) { for (int i = 0; i < xi.length; i++) { xi[i] = java.lang.Math.round(255 * (xi[i] + 1) / 2); } } Attribute[] attributes = new Attribute[256]; String[] values = new String[attributes.length]; for (int i = 0; i < attributes.length; i++) { values[i] = String.valueOf(i); } for (int i = 0; i < attributes.length; i++) { attributes[i] = new NominalAttribute("V" + i, values); } RandomForest forest = new RandomForest(attributes, x, y, 200); int error = 0; for (int i = 0; i < testx.length; i++) { if (forest.predict(testx[i]) != testy[i]) { error++; } } assertTrue(error <= 250); }