info.c

C4.5决策树算法C语言实现

/*************************************************************************/
/*									 */
/*	Calculate information, information gain, and print dists	 */
/*	--------------------------------------------------------	 */
/*									 */
/*************************************************************************/


#include "buildex.i"


/*************************************************************************/
/*									 */
/*  Determine the worth of a particular split according to the		 */
/*  operative criterion							 */
/*									 */
/*	    Parameters:							 */
/*		SplitInfo:	potential info of the split		 */
/*		SplitGain:	gain in info of the split		 */
/*		MinGain:	gain above which the Gain Ratio		 */
/*				may be used				 */
/*									 */
/*  If the Gain criterion is being used, the information gain of	 */
/*  the split is returned, but if the Gain Ratio criterion is		 */
/*  being used, the ratio of the information gain of the split to	 */
/*  its potential information is returned.				 */
/*									 */
/*************************************************************************/

float TotalInfo(ItemCount V[],DiscrValue MinVal,DiscrValue MaxVal);

float Worth(float ThisInfo,float ThisGain,float MinGain)
/*    -----  */
{
    if ( GAINRATIO )
    {
	if ( ThisGain >= MinGain - Epsilon && ThisInfo > Epsilon )
	{
	    return ThisGain / ThisInfo;
	}
	else
	{
	    return -(float)Epsilon;
	}
    }
    else
    {
	return ( ThisInfo > 0 && ThisGain > -(float)Epsilon ? ThisGain : -(float)Epsilon );
    }
}



/*************************************************************************/
/*									 */
/*  Zero the frequency tables Freq[][] and ValFreq[] up to MaxVal	 */
/*									 */
/*************************************************************************/


void    ResetFreq(DiscrValue MaxVal)
/*  ---------  */
{
    DiscrValue v;
    ClassNo c;

    ForEach(v, 0, MaxVal)
    { 
	ForEach(c, 0, MaxClass)
	{
	    Freq[v][c] = 0;
	}
	ValFreq[v] = 0;
    } 
}



/*************************************************************************/
/*									 */
/*  Given tables Freq[][] and ValFreq[], compute the information gain.	 */
/*									 */
/*	    Parameters:							 */
/*		BaseInfo:	average information for all items with	 */
/*				known values of the test attribute	 */
/*		UnknownRate:	fraction of items with unknown ditto	 */
/*		MaxVal:		number of forks				 */
/*		TotalItems:	number of items with known values of	 */
/*				test att				 */
/*									 */
/*  where Freq[x][y] contains the no. of cases with value x for a	 */
/*  particular attribute that are members of class y,			 */
/*  and ValFreq[x] contains the no. of cases with value x for a		 */
/*  particular attribute						 */
/*									 */
/*************************************************************************/


float ComputeGain(float BaseInfo,float UnknFrac,DiscrValue MaxVal,ItemCount TotalItems)
/*    -----------  */
{
    DiscrValue v;
    float ThisInfo=0.0, ThisGain;
    short ReasonableSubsets=0;

    /*  Check whether all values are unknown or the same  */

    if ( ! TotalItems ) return -(float)Epsilon;

    /*  There must be at least two subsets with MINOBJS items  */

    ForEach(v, 1, MaxVal)
    {
	if ( ValFreq[v] >= MINOBJS ) ReasonableSubsets++;
    }
    if ( ReasonableSubsets < 2 ) return -(float)Epsilon;

    /*  Compute total info after split, by summing the
	info of each of the subsets formed by the test  */

    ForEach(v, 1, MaxVal)
    {
	ThisInfo += TotalInfo(Freq[v], 0, MaxClass);
    }

    /*  Set the gain in information for all items, adjusted for unknowns  */

    ThisGain = (1 - UnknFrac) * (BaseInfo - ThisInfo / TotalItems);

    Verbosity(5)
        printf("ComputeThisGain: items %.1f info %.3f base %.3f unkn %.3f result %.3f\n",
    		TotalItems + ValFreq[0], ThisInfo, BaseInfo, UnknFrac, ThisGain);

    return ThisGain;
}



/*************************************************************************/
/*									 */
/*  Compute the total information in V[ MinVal..MaxVal ]		 */
/*									 */
/*************************************************************************/


float TotalInfo(ItemCount V[],DiscrValue MinVal,DiscrValue MaxVal)
/*    ---------  */
{
    DiscrValue v;
    float Sum=0.0;
    ItemCount N, TotalItems=0;

    ForEach(v, MinVal, MaxVal)
    {
	N = V[v];

	Sum += N * (float) Log(N);
	TotalItems += N;
    }

    return TotalItems *(float) Log(TotalItems) - Sum;
}



/*************************************************************************/
/*									 */
/*	Print distribution table for given attribute			 */
/*									 */
/*************************************************************************/


void    PrintDistribution(Attribute Att,DiscrValue MaxVal,Boolean ShowNames)
/*  -----------------  */
{
    DiscrValue v;
    ClassNo c;
    String Val;

    printf("\n\t\t\t ");
    ForEach(c, 0, MaxClass)
    {
	printf("%7.6s", ClassName[c]);
    }
    printf("\n");

    ForEach(v, 0, MaxVal)
    {
	if ( ShowNames )
	{
	    Val = ( !v ? "unknown" :
		    MaxAttVal[Att] ? AttValName[Att][v] :
		    v == 1 ? "below" : "above" );
	    printf("\t\t[%-7.7s:", Val);
	}
	else
	{
	    printf("\t\t[%-7d:", v);
	}

	ForEach(c, 0, MaxClass)
	{
	    printf(" %6.1f", Freq[v][c]);
	}

	printf("]\n");
    }
}