| /* |
| * 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.perceptron; |
| |
| import opennlp.tools.ml.ArrayMath; |
| import opennlp.tools.ml.model.AbstractModel; |
| import opennlp.tools.ml.model.Context; |
| import opennlp.tools.ml.model.EvalParameters; |
| |
| public class PerceptronModel extends AbstractModel { |
| |
| public PerceptronModel(Context[] params, String[] predLabels, String[] outcomeNames) { |
| super(params,predLabels,outcomeNames); |
| modelType = ModelType.Perceptron; |
| } |
| |
| public double[] eval(String[] context) { |
| return eval(context,new double[evalParams.getNumOutcomes()]); |
| } |
| |
| public double[] eval(String[] context, float[] values) { |
| return eval(context,values,new double[evalParams.getNumOutcomes()]); |
| } |
| |
| public double[] eval(String[] context, double[] probs) { |
| return eval(context,null,probs); |
| } |
| |
| public double[] eval(String[] context, float[] values,double[] outsums) { |
| Context[] scontexts = new Context[context.length]; |
| java.util.Arrays.fill(outsums, 0); |
| for (int i = 0; i < context.length; i++) { |
| scontexts[i] = pmap.get(context[i]); |
| } |
| return eval(scontexts,values,outsums,evalParams,true); |
| } |
| |
| public static double[] eval(int[] context, double[] prior, EvalParameters model) { |
| return eval(context,null,prior,model,true); |
| } |
| |
| static double[] eval(int[] context, float[] values, double[] prior, EvalParameters model, |
| boolean normalize) { |
| Context[] scontexts = new Context[context.length]; |
| for (int i = 0; i < context.length; i++) { |
| scontexts[i] = model.getParams()[context[i]]; |
| } |
| |
| return eval(scontexts, values, prior, model, normalize); |
| } |
| |
| static double[] eval(Context[] context, float[] values, double[] prior, EvalParameters model, |
| boolean normalize) { |
| |
| ArrayMath.sumFeatures(context, values, prior); |
| |
| if (normalize) { |
| int numOutcomes = model.getNumOutcomes(); |
| |
| double maxPrior = 1; |
| |
| for (int oid = 0; oid < numOutcomes; oid++) { |
| if (maxPrior < StrictMath.abs(prior[oid])) |
| maxPrior = StrictMath.abs(prior[oid]); |
| } |
| |
| double normal = 0.0; |
| for (int oid = 0; oid < numOutcomes; oid++) { |
| prior[oid] = StrictMath.exp(prior[oid] / maxPrior); |
| normal += prior[oid]; |
| } |
| |
| for (int oid = 0; oid < numOutcomes; oid++) { |
| prior[oid] /= normal; |
| } |
| } |
| return prior; |
| } |
| } |