Package com.digitalpebble.classification.test

Source Code of com.digitalpebble.classification.test.TestTrainingCorpus

/**
* Copyright 2009 DigitalPebble Ltd
*
* Licensed 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 com.digitalpebble.classification.test;

import java.util.Iterator;

import com.digitalpebble.classification.Document;
import com.digitalpebble.classification.Field;
import com.digitalpebble.classification.RAMTrainingCorpus;

public class TestTrainingCorpus extends AbstractLearnerTest {

  public void testMultiField() throws Exception {
    Field[] fields = new Field[3];
    fields[0] = new Field("title", new String[] { "This", "is", "a",
        "title" });
    fields[1] = new Field("abstract", new String[] { "abstract" });
    fields[2] = new Field("content", new String[] { "This", "is", "the",
        "content", "this", "will", "have", "a", "large", "value" });
    Document doc = learner.createDocument(fields, "large");

    String[] simplecontent = new String[] { "This", "is", "the", "content",
        "this", "will", "have", "a", "small", "value" };
    Document doc2 = learner.createDocument(simplecontent, "small");

    // com.digitalpebble.classification.TrainingCorpus tc =
    // learner.getFileTrainingCorpus();
    com.digitalpebble.classification.TrainingCorpus tc = new RAMTrainingCorpus();
    tc.addDocument(doc);
    tc.addDocument(doc2);
    tc.close();

    int numDoc = 0;

    Iterator iter = tc.iterator();
    while (iter.hasNext()) {
      numDoc++;
      iter.next();
    }

    assertEquals(2, numDoc);

    tc = learner.getFileTrainingCorpus();
    tc.addDocument(doc);
    tc.addDocument(doc2);
    tc.close();

    numDoc = 0;

    iter = tc.iterator();
    while (iter.hasNext()) {
      numDoc++;
      iter.next();
    }

    assertEquals(2, numDoc);

    learner.learn(tc);

  }

}
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