modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMMultiClassTrainerTest.java

   1 /*
   2  * Licensed to the Apache Software Foundation (ASF) under one or more
   3  * contributor license agreements.  See the NOTICE file distributed with
   4  * this work for additional information regarding copyright ownership.
   5  * The ASF licenses this file to You under the Apache License, Version 2.0
   6  * (the "License"); you may not use this file except in compliance with
   7  * the License.  You may obtain a copy of the License at
   8  *
   9  *      http://www.apache.org/licenses/LICENSE-2.0
  10  *
  11  * Unless required by applicable law or agreed to in writing, software
  12  * distributed under the License is distributed on an "AS IS" BASIS,
  13  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  14  * See the License for the specific language governing permissions and
  15  * limitations under the License.
  16  */
  17
  18 package org.apache.ignite.ml.svm;
  19
  20 import java.util.Arrays;
  21 import java.util.HashMap;
  22 import java.util.Map;
  23 import java.util.concurrent.ThreadLocalRandom;
  24 import org.apache.ignite.ml.TestUtils;
  25 import org.apache.ignite.ml.math.VectorUtils;
  26 import org.apache.ignite.ml.math.impls.vector.DenseLocalOnHeapVector;
  27 import org.junit.Test;
  28
  29 /**
  30  * Tests for {@link SVMLinearBinaryClassificationTrainer}.
  31  */
  32 public class SVMMultiClassTrainerTest {
  33     /** Fixed size of Dataset. */
  34     private static final int AMOUNT_OF_OBSERVATIONS = 1000;
  35
  36     /** Fixed size of columns in Dataset. */
  37     private static final int AMOUNT_OF_FEATURES = 2;
  38
  39     /** Precision in test checks. */
  40     private static final double PRECISION = 1e-2;
  41
  42     /**
  43      * Test trainer on classification model y = x.
  44      */
  45     @Test
  46     public void testTrainWithTheLinearlySeparableCase() {
  47         Map<Integer, double[]> data = new HashMap<>();
  48
  49         ThreadLocalRandom rndX = ThreadLocalRandom.current();
  50         ThreadLocalRandom rndY = ThreadLocalRandom.current();
  51
  52         for (int i = 0; i < AMOUNT_OF_OBSERVATIONS; i++) {
  53             double x = rndX.nextDouble(-1000, 1000);
  54             double y = rndY.nextDouble(-1000, 1000);
  55             double[] vec = new double[AMOUNT_OF_FEATURES + 1];
  56             vec[0] = y - x > 0 ? 1 : -1; // assign label.
  57             vec[1] = x;
  58             vec[2] = y;
  59             data.put(i, vec);
  60         }
  61
  62         SVMLinearMultiClassClassificationTrainer trainer = new SVMLinearMultiClassClassificationTrainer()
  63             .withLambda(0.3)
  64             .withAmountOfLocIterations(100)
  65             .withAmountOfIterations(20);
  66
  67         SVMLinearMultiClassClassificationModel mdl = trainer.fit(
  68             data,
  69             10,
  70             (k, v) -> VectorUtils.of(Arrays.copyOfRange(v, 1, v.length)),
  71             (k, v) -> v[0]
  72         );
  73
  74         TestUtils.assertEquals(-1, mdl.apply(new DenseLocalOnHeapVector(new double[]{100, 10})), PRECISION);
  75         TestUtils.assertEquals(1, mdl.apply(new DenseLocalOnHeapVector(new double[]{10, 100})), PRECISION);
  76     }
  77 }