actual_error.txt

包含了模式识别中常用的一些分类器设计算法

// function to calculate the actual error
// method : actual_error
// arguments : vector, vector, double
// return : void
// description :
// Compute the actual error from the given data points and the estimated
// values.
//----------------------------------------------------------------
public void actual_error( Vector y_estimate, Vector iset, double act_error)
{
//	double actual_pt[];
//	double estimate_pt[];	
	double error_value;
	int j = 0;
	
	for (int i = 0; (i < y_estimate.size() && j < iset.size() ); i++)
	{
		while ( ((MyPoint)y_estimate.elementAt(i)).x < ((MyPoint)iset.elementAt(j)).x )
		      if ( ( i < y_estimate.size() ) && ( j < iset.size() )
			 i++;
	              else
			 break;

		if ( j < iset.size())
		{
		   if ( ((MyPoint)y_estimate.elementAt(i)).x == ((MyPoint)iset.elementAt(j)).x ) 
		   {
			// error is -
			error_value = ((MyPoint)y_estimate.elementAt(i)).y - ((MyPoint)iset.elementAt(j)).y;
			act_error += error_value * err_value;
		    }
		    if ( ((MyPoint)y_estimate.elementAt(i)).x > ((MyPoint)iset.elementAt(j)).x )
		    {
			double y1 = ((MyPoint)y_estimate.elementAt(i)).y;
			double y2 = ((MyPoint)y_estimate.elementAt(i - 1)).y;
			double x1 = ((MyPoint)y_estimate.elementAt(i)).x;
			double x2 = ((MyPoint)y_estimate.elementAt(i - 1)).x;
			double x_unknown = ((MyPoint)iset.elementAt(j)).x
			error_value = y2 - ( (x2 - x_unknown) * ( y2 - y1) / (x2 - x1));
			act_error += error_value * error_value ;
		    }
		    j++;
		}

	}	
	
}