DecisionTreeTest.java

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 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing,
 * software distributed under the License is distributed on an
 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
 * KIND, either express or implied.  See the License for the
 * specific language governing permissions and limitations
 * under the License.
 */
package hivemall.smile.classification;

import static org.junit.Assert.assertEquals;
import hivemall.smile.ModelType;
import hivemall.smile.classification.DecisionTree.Node;
import hivemall.smile.data.Attribute;
import hivemall.smile.tools.TreePredictUDF;
import hivemall.smile.utils.SmileExtUtils;
import hivemall.smile.vm.StackMachine;
import hivemall.utils.lang.ArrayUtils;

import java.io.BufferedInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.net.URL;
import java.text.ParseException;

import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDF.DeferredJavaObject;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDF.DeferredObject;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorUtils;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.io.IntWritable;
import org.junit.Assert;
import org.junit.Test;

import smile.data.AttributeDataset;
import smile.data.parser.ArffParser;
import smile.math.Math;
import smile.validation.LOOCV;

public class DecisionTreeTest {
    private static final boolean DEBUG = false;

    /**
     * Test of learn method, of class DecisionTree.
     * 
     * @throws ParseException
     * @throws IOException
     */
    @Test
    public void testWeather() throws IOException, ParseException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/2c9df50db3de93a71b92/raw/3f6b4ecfd4045008059e1a2d1c4064fb8a3d372a/weather.nominal.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);

        AttributeDataset weather = arffParser.parse(is);
        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]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(weather.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 3);
            if (y[loocv.test[i]] != tree.predict(x[loocv.test[i]]))
                error++;
        }

        debugPrint("Decision Tree error = " + error);
        assertEquals(5, error);
    }

    @Test
    public void testIris() throws IOException, ParseException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);

        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.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]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            smile.math.Random rand = new smile.math.Random(i);
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, Integer.MAX_VALUE, rand);
            if (y[loocv.test[i]] != tree.predict(x[loocv.test[i]]))
                error++;
        }

        debugPrint("Decision Tree error = " + error);
        assertEquals(8, error);
    }

    @Test
    public void testIrisDepth4() throws IOException, ParseException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);

        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.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]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 4);
            if (y[loocv.test[i]] != tree.predict(x[loocv.test[i]]))
                error++;
        }

        debugPrint("Decision Tree error = " + error);
        assertEquals(7, error);
    }

    @Test
    public void testIrisStackmachine() throws IOException, ParseException, HiveException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);
        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);

        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 4);
            assertEquals(tree.predict(x[loocv.test[i]]),
                predictByStackMachine(tree, x[loocv.test[i]]));
        }
    }

    @Test
    public void testIrisJavascript() throws IOException, ParseException, HiveException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);
        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);

        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 4);
            assertEquals(tree.predict(x[loocv.test[i]]),
                predictByJavascript(tree, x[loocv.test[i]]));
        }
    }

    @Test
    public void testIrisSerializedObj() throws IOException, ParseException, HiveException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);
        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);

        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 4);

            byte[] b = tree.predictSerCodegen(false);
            Node node = DecisionTree.deserializeNode(b, b.length, false);
            assertEquals(tree.predict(x[loocv.test[i]]), node.predict(x[loocv.test[i]]));
        }
    }

    @Test
    public void testIrisSerializeObjCompressed() throws IOException, ParseException, HiveException {
        URL url = new URL(
            "https://gist.githubusercontent.com/myui/143fa9d05bd6e7db0114/raw/500f178316b802f1cade6e3bf8dc814a96e84b1e/iris.arff");
        InputStream is = new BufferedInputStream(url.openStream());

        ArffParser arffParser = new ArffParser();
        arffParser.setResponseIndex(4);
        AttributeDataset iris = arffParser.parse(is);
        double[][] x = iris.toArray(new double[iris.size()][]);
        int[] y = iris.toArray(new int[iris.size()]);

        int n = x.length;
        LOOCV loocv = new LOOCV(n);
        for (int i = 0; i < n; i++) {
            double[][] trainx = Math.slice(x, loocv.train[i]);
            int[] trainy = Math.slice(y, loocv.train[i]);

            Attribute[] attrs = SmileExtUtils.convertAttributeTypes(iris.attributes());
            DecisionTree tree = new DecisionTree(attrs, trainx, trainy, 4);

            byte[] b1 = tree.predictSerCodegen(true);
            byte[] b2 = tree.predictSerCodegen(false);
            Assert.assertTrue("b1.length = " + b1.length + ", b2.length = " + b2.length,
                b1.length < b2.length);
            Node node = DecisionTree.deserializeNode(b1, b1.length, true);
            assertEquals(tree.predict(x[loocv.test[i]]), node.predict(x[loocv.test[i]]));
        }
    }

    private static int predictByStackMachine(DecisionTree tree, double[] x) throws HiveException,
            IOException {
        String script = tree.predictOpCodegen(StackMachine.SEP);
        debugPrint(script);

        TreePredictUDF udf = new TreePredictUDF();
        udf.initialize(new ObjectInspector[] {
                PrimitiveObjectInspectorFactory.javaStringObjectInspector,
                PrimitiveObjectInspectorFactory.javaIntObjectInspector,
                PrimitiveObjectInspectorFactory.javaStringObjectInspector,
                ObjectInspectorFactory.getStandardListObjectInspector(PrimitiveObjectInspectorFactory.javaDoubleObjectInspector),
                ObjectInspectorUtils.getConstantObjectInspector(
                    PrimitiveObjectInspectorFactory.javaBooleanObjectInspector, true)});
        DeferredObject[] arguments = new DeferredObject[] {new DeferredJavaObject("model_id#1"),
                new DeferredJavaObject(ModelType.opscode.getId()), new DeferredJavaObject(script),
                new DeferredJavaObject(ArrayUtils.toList(x)), new DeferredJavaObject(true)};

        IntWritable result = (IntWritable) udf.evaluate(arguments);
        result = (IntWritable) udf.evaluate(arguments);
        udf.close();
        return result.get();
    }

    private static int predictByJavascript(DecisionTree tree, double[] x) throws HiveException,
            IOException {
        String script = tree.predictJsCodegen();
        debugPrint(script);

        TreePredictUDF udf = new TreePredictUDF();
        udf.initialize(new ObjectInspector[] {
                PrimitiveObjectInspectorFactory.javaStringObjectInspector,
                PrimitiveObjectInspectorFactory.javaIntObjectInspector,
                PrimitiveObjectInspectorFactory.javaStringObjectInspector,
                ObjectInspectorFactory.getStandardListObjectInspector(PrimitiveObjectInspectorFactory.javaDoubleObjectInspector),
                ObjectInspectorUtils.getConstantObjectInspector(
                    PrimitiveObjectInspectorFactory.javaBooleanObjectInspector, true)});

        DeferredObject[] arguments = new DeferredObject[] {new DeferredJavaObject("model_id#1"),
                new DeferredJavaObject(ModelType.javascript.getId()),
                new DeferredJavaObject(script), new DeferredJavaObject(ArrayUtils.toList(x)),
                new DeferredJavaObject(true)};

        IntWritable result = (IntWritable) udf.evaluate(arguments);
        result = (IntWritable) udf.evaluate(arguments);
        udf.close();
        return result.get();
    }

    private static void debugPrint(String msg) {
        if (DEBUG) {
            System.out.println(msg);
        }
    }

}