AbstractLiblinear.java

/**
 * Copyright 2014, Emory University
 * 
 * Licensed 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 edu.emory.clir.clearnlp.classification.trainer;

import edu.emory.clir.clearnlp.classification.model.SparseModel;
import edu.emory.clir.clearnlp.classification.model.StringModel;


/**
 * @since 3.0.0
 * @author Jinho D. Choi ({@code jinho.choi@emory.edu})
 */
abstract public class AbstractLiblinear extends AbstractOneVsAllTrainer
{
	protected final int MAX_ITER = 1000;
	
	protected double d_cost;
	protected double d_eps;
	protected double d_bias;
	
	public AbstractLiblinear(SparseModel model, int numThreads, double cost, double eps, double bias)
	{
		super(model, numThreads);
		init(cost, eps, bias);
	}
	
	public AbstractLiblinear(StringModel model, int labelCutoff, int featureCutoff, int numThreads, double cost, double eps, double bias)
	{
		super(model, labelCutoff, featureCutoff, numThreads);
		init(cost, eps, bias);
	}
	
	private void init(double cost, double eps, double bias)
	{
		d_cost = cost;
		d_eps  = eps;
		d_bias = (bias > 0) ? bias : 0;
	}
	
	public String trainerInfo(String type)
	{
		return String.format("Liblinear-%s: cost = %4.3f, eps = %4.3f, bias = %b", type, d_cost, d_eps, d_bias);
	}
}