//******************************************************************************
//  This component produced by Rough Enough version 4.0
//  utilizing Object Mining technology introduced by Anders Torvill Bjorvand
//******************************************************************************
//  Rough Enough is (C)opyright of Troll Data Inc in Norway which can be
//  reached at email: support@trolldata.no
//             www:   http://www.trolldata.com/
//******************************************************************************
//  Rules-method:1: Voting with inexact rules
//******************************************************************************
//  Time of generation: 05:10:32 PM, 08/24/98
//******************************************************************************

public class dogs implements java.io.Serializable
{
	// Property declarations
	protected int AttributeDecision = 0;
	protected int AttributeTail = 0;
	protected int AttributeHair = 0;

	private int decisionPower = -1;
	private int decisionIndex = -1;
	private int[] predictions;
	private boolean match;

	// Ruleset
	private int ruleSetSize = 6;
	private int numberOfConditionalAttributes = 2;
	private int numberOfDecisionValues = 4;
	protected int[][] ruleSet = {
		{-1,	2,	4,	1,	0},
		{-1,	3,	3,	1,	0},
		{1,	1,	1,	1,	0},
		{1,	3,	3,	1,	0},
		{2,	1,	2,	1,	0},
		{2,	2,	4,	1,	0},
	};

	// Constructor
	public dogs()
	{
	}

	protected void calculateDecision()
	{
		decisionPower = -1;
		decisionIndex = -1;
		predictions = new int[numberOfDecisionValues];
		for(int i = 0; i<numberOfDecisionValues ; i++)
		{
			predictions[i] = 0;
		}
		for(int i = 0; i<ruleSetSize ; i++)
		{
			match = true;
			for(int j = 0; j<numberOfConditionalAttributes ; j++)
			{
				if(ruleSet[i][j] != -1)
				{
					if(ruleSet[i][j] != getAttributeByIndex(j+1))
					{
						match = false;
					}
				}
			}
			if(match == true)
			{
				predictions[ruleSet[i][numberOfConditionalAttributes]-1] = predictions[ruleSet[i][numberOfConditionalAttributes]-1] + ruleSet[i][numberOfConditionalAttributes+1] - ruleSet[i][numberOfConditionalAttributes+2];
			}
		}
		for(int i=1; i<=numberOfDecisionValues; i++)
		{
			if(predictions[i-1] > decisionPower)
			{
				decisionPower = predictions[i-1];
				decisionIndex = i;
			}
		}
		if(decisionIndex == -1)
		{
			AttributeDecision = 0;
		}
		else
		{
			AttributeDecision = decisionIndex;
		}
	}
	public void setAttributeTail(int attribute_value)
	{
		AttributeTail = attribute_value;
	}

	public int getAttributeTail()
	{
		return AttributeTail;
	}

	public void setAttributeHair(int attribute_value)
	{
		AttributeHair = attribute_value;
	}

	public int getAttributeHair()
	{
		return AttributeHair;
	}

	private int getAttributeByIndex(int attributeIndex)
	{
		switch(attributeIndex)
		{
			case 1:
				{
					return getAttributeTail();
				}
			case 2:
				{
					return getAttributeHair();
				}
			default:
				{
	return -1;
				}
		}
	}

	public int getAttributeDecision()
	{
		calculateDecision();
		return AttributeDecision;
	}
}