/*
* 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 opennlp.maxent;
import static opennlp.PrepAttachDataUtil.createTrainingStream;
import static opennlp.PrepAttachDataUtil.testModel;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import opennlp.model.AbstractModel;
import opennlp.model.TrainUtil;
import opennlp.model.TwoPassDataIndexer;
import opennlp.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 );
}
}