opennlp.tools.ml.model.EvalParameters 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.model;
import java.util.Arrays;
import java.util.Objects;
/**
* This class encapsulates the variables used in producing probabilities from a model
* and facilitates passing these variables to the eval method.
*/
public class EvalParameters {
/**
* Mapping between outcomes and parameter values for each context.
* The integer representation of the context can be found using pmap.
*/
private final Context[] params;
/**
* The number of outcomes being predicted.
*/
private final int numOutcomes;
/**
* The maximum number of features fired in an event. Usually referred to as C.
* This is used to normalize the number of features which occur in an event. */
private double correctionConstant;
public EvalParameters(Context[] params, int numOutcomes) {
this.params = params;
this.numOutcomes = numOutcomes;
}
public Context[] getParams() {
return params;
}
public int getNumOutcomes() {
return numOutcomes;
}
@Override
public int hashCode() {
return Objects.hash(Arrays.hashCode(params), numOutcomes, correctionConstant);
}
@Override
public boolean equals(Object obj) {
if (obj == this) {
return true;
}
if (obj instanceof EvalParameters evalParameters) {
return Arrays.equals(params, evalParameters.params)
&& numOutcomes == evalParameters.numOutcomes
&& correctionConstant == evalParameters.correctionConstant;
}
return false;
}
}