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Implementation of linear-chain Conditional Random Fields (CRF) in pure Java

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package com.asher_stern.crf.smalltests;

//import org.apache.log4j.Level;
//
//import com.asher_stern.crf.function.DerivableFunction;
//import com.asher_stern.crf.function.optimization.LbfgsMinimizer;
//import com.asher_stern.crf.function.optimization.Minimizer;
//import com.asher_stern.crf.utilities.StringUtilities;
//import com.asher_stern.crf.utilities.log4j.Log4jInit;

/**
 * 
 * @author Asher Stern
 * Date: Nov 6, 2014
 *
 */
public class DemoOptimizer
{
//
//	public static void main(String[] args)
//	{
//		try
//		{
//			Log4jInit.init(Level.DEBUG);
//			new DemoOptimizer().go();			
//		}
//		catch(Throwable t)
//		{
//			t.printStackTrace(System.out);
//		}
//
//	}
//	
//
//	public void go()
//	{
//		DerivableFunction function = createFunction();
//		//Optimizer optimizer = new GradientDescentOptimizer(function);
//		Minimizer optimizer = new LbfgsMinimizer(function);
//		optimizer.find();
//		
//		System.out.println("point = "+StringUtilities.arrayOfDoubleToString(optimizer.getPoint()));
//		System.out.println("value = "+String.format("%-3.3f",optimizer.getValue()));
//	}
//	
////	private DerivableFunction createFunction()
////	{
////		// (x+2)^2
////		DerivableFunction function = new DerivableFunction()
////		{
////			@Override
////			public double value(double[] point)
////			{
////				return (point[0]+2.0)*(point[0]+2.0);
////			}
////			
////			@Override
////			public int size()
////			{
////				return 1;
////			}
////			
////			@Override
////			public double[] gradient(double[] point)
////			{
////				return new double[]{2.0*(point[0]+2.0)};
////			}
////		};
////		
////		return function;
////	}
//
//	
//	
//	private DerivableFunction createFunction()
//	{
//		// (x_1-2)^2 + (2-x_2)^2 + x_1*x_2
//		DerivableFunction function = new DerivableFunction()
//		{
//			@Override
//			public double value(double[] point)
//			{
//				return (point[0]-2.0)*(point[0]-2.0)+(2.0-point[1])*(2.0-point[1])+point[0]*point[1];
//			}
//			
//			@Override
//			public int size()
//			{
//				return 2;
//			}
//			
//			@Override
//			public double[] gradient(double[] point)
//			{
//				return new double[]{2.0*(point[0]-2.0)+point[1], -2.0*(2.0-point[1])+point[0]};
//			}
//		};
//		
//		return function;
//	}

}