opennlp.tools.langdetect.LanguageDetectorEvaluator Maven / Gradle / Ivy
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* 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,
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* See the License for the specific language governing permissions and
* limitations under the License.
*/
package opennlp.tools.langdetect;
import opennlp.tools.doccat.DocumentCategorizer;
import opennlp.tools.util.eval.Evaluator;
import opennlp.tools.util.eval.Mean;
/**
* The {@link LanguageDetectorEvaluator} measures the performance of
* the given {@link LanguageDetector} with the provided reference
* {@link LanguageSample}s.
*
* @see LanguageDetector
* @see LanguageSample
*/
public class LanguageDetectorEvaluator extends Evaluator {
private final LanguageDetector languageDetector;
private final Mean accuracy = new Mean();
/**
* Initializes an instance to evaluate a {@link LanguageDetector}.
*
* @param langDetect the {@link LanguageDetector} to evaluate.
* @param listeners the {@link LanguageDetectorEvaluationMonitor evaluation listeners}.
*/
public LanguageDetectorEvaluator(LanguageDetector langDetect,
LanguageDetectorEvaluationMonitor ... listeners) {
super(listeners);
this.languageDetector = langDetect;
}
/**
* Evaluates the given reference {@link LanguageSample} object.
* This is achieved by categorizing the document of the provided
* {@link LanguageSample}. The detected language is then used
* to calculate and update the score.
*
* @param sample the reference {@link LanguageSample}.
* @return The processed {@link LanguageSample}.
*/
public LanguageSample processSample(LanguageSample sample) {
CharSequence document = sample.context();
Language predicted = languageDetector.predictLanguage(document);
if (sample.language().getLang().equals(predicted.getLang())) {
accuracy.add(1);
}
else {
accuracy.add(0);
}
return new LanguageSample(predicted, sample.context());
}
/**
* @return Retrieves the accuracy of provided {@link DocumentCategorizer}.
* Here: {@code accuracy = correctly categorized documents / total documents}.
*/
public double getAccuracy() {
return accuracy.mean();
}
public long getDocumentCount() {
return accuracy.count();
}
/**
* Represents this object as human-readable {@link String}.
*/
@Override
public String toString() {
return "Accuracy: " + accuracy.mean() + "\n" +
"Number of documents: " + accuracy.count();
}
}