opennlp-ml/src/test/java/org/apache/opennlp/ml/maxent/MaxentPrepAttachTest.java

/*
 * 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.
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package org.apache.opennlp.ml.maxent;

import static org.apache.opennlp.ml.PrepAttachDataUtil.createTrainingStream;
import static org.apache.opennlp.ml.PrepAttachDataUtil.testModel;

import java.io.IOException;
import java.util.HashMap;
import java.util.Map;


import org.apache.opennlp.ml.model.AbstractModel;
import org.apache.opennlp.ml.model.TrainUtil;
import org.apache.opennlp.ml.model.TwoPassDataIndexer;
import org.apache.opennlp.ml.model.UniformPrior;
import org.junit.Test;

public class MaxentPrepAttachTest {

  @Test
  public void testMaxentOnPrepAttachData() throws IOException {
    AbstractModel model = 
        new GISTrainer(true).trainModel(100, 
        new TwoPassDataIndexer(createTrainingStream(), 1), 1);

    testModel(model, 0.7997028967566229);
  }
  
  @Test
  public void testMaxentOnPrepAttachData2Threads() throws IOException {
    AbstractModel model = 
        new GISTrainer(true).trainModel(100,
            new TwoPassDataIndexer(createTrainingStream(), 1),
            new UniformPrior(), 1, 2);
    
    testModel(model, 0.7997028967566229);
  }
  
  @Test
  public void testMaxentOnPrepAttachDataWithParams() throws IOException {
    
    Map<String, String> trainParams = new HashMap<String, String>();
    trainParams.put(TrainUtil.ALGORITHM_PARAM, TrainUtil.MAXENT_VALUE);
    trainParams.put(TrainUtil.DATA_INDEXER_PARAM,
        TrainUtil.DATA_INDEXER_TWO_PASS_VALUE);
    trainParams.put(TrainUtil.CUTOFF_PARAM, Integer.toString(1));
    
    AbstractModel model = TrainUtil.train(createTrainingStream(), trainParams, null);
    
    testModel(model, 0.7997028967566229);
  }
  
  @Test
  public void testMaxentOnPrepAttachDataWithParamsDefault() throws IOException {
    
    Map<String, String> trainParams = new HashMap<String, String>();
    trainParams.put(TrainUtil.ALGORITHM_PARAM, TrainUtil.MAXENT_VALUE);
    
    AbstractModel model = TrainUtil.train(createTrainingStream(), trainParams, null);
    
    testModel(model, 0.8086159940579352 );
  }
  
}