opennlp.tools.ml.naivebayes.NaiveBayesModelWriter 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.ml.naivebayes;
import java.io.IOException;
import java.util.Arrays;
import java.util.Map;
import opennlp.tools.ml.AbstractMLModelWriter;
import opennlp.tools.ml.model.AbstractModel;
import opennlp.tools.ml.model.AbstractModelWriter;
import opennlp.tools.ml.model.ComparablePredicate;
import opennlp.tools.ml.model.Context;
/**
* The base class for {@link NaiveBayesModel} writers.
*
* It provides the {@link #persist()} method which takes care of the structure
* of a stored document, and requires an extending class to define precisely
* how the data should be stored.
*
* @see NaiveBayesModel
* @see AbstractModelWriter
* @see AbstractMLModelWriter
*/
public abstract class NaiveBayesModelWriter extends AbstractMLModelWriter {
/**
* Initializes a {@link NaiveBayesModelWriter} for a
* {@link AbstractModel NaiveBayes model}.
*
* @param model The {@link AbstractModel NaiveBayes model} to be written.
*/
public NaiveBayesModelWriter(AbstractModel model) {
super();
Object[] data = model.getDataStructures();
this.numOutcomes = model.getNumOutcomes();
PARAMS = (Context[]) data[0];
@SuppressWarnings("unchecked")
Map pmap = (Map) data[1];
OUTCOME_LABELS = (String[]) data[2];
PARAMS = new Context[pmap.size()];
PRED_LABELS = new String[pmap.size()];
int i = 0;
for (Map.Entry pred : pmap.entrySet()) {
PRED_LABELS[i] = pred.getKey();
PARAMS[i] = pred.getValue();
i++;
}
}
/**
* {@inheritDoc}
*/
@Override
protected ComparablePredicate[] sortValues() {
ComparablePredicate[] sortPreds = new ComparablePredicate[PARAMS.length];
int numParams = 0;
for (int pid = 0; pid < PARAMS.length; pid++) {
int[] predkeys = PARAMS[pid].getOutcomes();
// Arrays.sort(predkeys);
int numActive = predkeys.length;
double[] activeParams = PARAMS[pid].getParameters();
numParams += numActive;
/*
* double[] activeParams = new double[numActive];
*
* int id = 0; for (int i=0; i < predkeys.length; i++) { int oid =
* predkeys[i]; activeOutcomes[id] = oid; activeParams[id] =
* PARAMS[pid].getParams(oid); id++; }
*/
sortPreds[pid] = new ComparablePredicate(PRED_LABELS[pid],
predkeys, activeParams);
}
Arrays.sort(sortPreds);
return sortPreds;
}
/**
* Writes the {@link AbstractModel perceptron model}, using the
* {@link #writeUTF(String)}, {@link #writeDouble(double)}, or {@link #writeInt(int)}}
* methods implemented by extending classes.
*
* If you wish to create a {@link NaiveBayesModelWriter} which uses a different
* structure, it will be necessary to override the {@link #persist()} method in
* addition to implementing the {@code writeX(..)} methods.
*
* @throws IOException Thrown if IO errors occurred.
*/
@Override
public void persist() throws IOException {
// the type of model (NaiveBayes)
writeUTF("NaiveBayes");
super.persist();
}
}