confmat.cpp

One kind of decision-making tree algorithm, can be seen as one kind data mining algorithm ,find the

/*************************************************************************/
/*                                                                       */
/*      Routine for printing confusion matrices                          */
/*      ---------------------------------------                          */
/*                                                                       */
/*************************************************************************/

#include "defns.h"
#include "c45types.h"
#include "extern.h"

extern FILE *fpScreen;


void PrintConfusionMatrix(ItemNo * ConfusionMat)
/*  --------------------  */    
{
    int Row, Col;

    /*  Print the heading, then each row  */

    fprintf(fpScreen,"\n\n\t");
        printf("\n\n\t");
    ForEach(Col, 0, MaxClass)
    {
                fprintf(fpScreen,"  (%c)", 'a' + Col);
                printf("  (%c)", 'a' + Col);
    }

    fprintf(fpScreen,"\t<-classified as\n\t");
        printf("\t<-classified as\n\t");
    ForEach(Col, 0, MaxClass)
    {
                fprintf(fpScreen," ----");
                printf(" ----");
    }
    fprintf(fpScreen,"\n");
        printf("\n");

    ForEach(Row, 0, MaxClass)
    {
        fprintf(fpScreen,"\t");
        printf("\t");
        ForEach(Col, 0, MaxClass)
        {
            if ( ConfusionMat[Row*(MaxClass+1) + Col] )
            {
                fprintf(fpScreen,"%5d", ConfusionMat[Row*(MaxClass+1) + Col]);
                printf("%5d", ConfusionMat[Row*(MaxClass+1) + Col]);
            }
            else
            {
                fprintf(fpScreen,"     ");
                printf("     ");
            }
        }
        fprintf(fpScreen,"\t(%c): class %s\n", 'a' + Row, ClassName[Row]);
        printf("\t(%c): class %s\n", 'a' + Row, ClassName[Row]);
    }
    fprintf(fpScreen,"\n");
        printf("\n");
}