opennlp.tools.util.eval.Evaluator Maven / Gradle / Ivy
/*
* 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.tools.util.eval;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import opennlp.tools.util.ObjectStream;
/**
* The {@link Evaluator} is an abstract base class for evaluators.
*
* Evaluation results are the arithmetic mean of the
* scores calculated for each reference sample.
*/
public abstract class Evaluator {
private List> listeners;
@SafeVarargs
public Evaluator(EvaluationMonitor... aListeners) {
if (aListeners != null) {
List> listenersList = new ArrayList<>(
aListeners.length);
for (EvaluationMonitor evaluationMonitor : aListeners) {
if (evaluationMonitor != null) {
listenersList.add(evaluationMonitor);
}
}
listeners = Collections.unmodifiableList(listenersList);
} else {
listeners = Collections.emptyList();
}
}
/**
* Evaluates the given reference sample object.
*
* The implementation has to update the score after every invocation.
*
* @param reference the reference sample.
*
* @return the predicted sample
*/
protected abstract T processSample(T reference);
/**
* Evaluates the given reference object. The default implementation calls
* {@link Evaluator#processSample(Object)}
*
*
* note: this method will be changed to private in the future.
* Implementations should override {@link Evaluator#processSample(Object)} instead.
* If this method is override, the implementation has to update the score
* after every invocation.
*
*
* @param sample
* the sample to be evaluated
*/
public void evaluateSample(T sample) {
T predicted = processSample(sample);
if(!listeners.isEmpty()) {
if(sample.equals(predicted)) {
for (EvaluationMonitor listener : listeners) {
listener.correctlyClassified(sample, predicted);
}
} else {
for (EvaluationMonitor listener : listeners) {
listener.missclassified(sample, predicted);
}
}
}
}
/**
* Reads all sample objects from the stream
* and evaluates each sample object with
* {@link #evaluateSample(Object)} method.
*
* @param samples the stream of reference which
* should be evaluated.
*
* @throws IOException IOException
*/
public void evaluate(ObjectStream samples) throws IOException {
T sample;
while ((sample = samples.read()) != null) {
evaluateSample(sample);
}
}
}