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📄 info.c

📁 c4.5的源码决策树最全面最经典的版本
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/*************************************************************************//*									 *//*	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 Worth(ThisInfo, ThisGain, MinGain)/*    -----  */    float ThisInfo, ThisGain, MinGain;{    if ( GAINRATIO )    {	if ( ThisGain >= MinGain - Epsilon && ThisInfo > Epsilon )	{	    return ThisGain / ThisInfo;	}	else	{	    return -Epsilon;	}    }    else    {	return ( ThisInfo > 0 && ThisGain > -Epsilon ? ThisGain : -Epsilon );    }}/*************************************************************************//*									 *//*  Zero the frequency tables Freq[][] and ValFreq[] up to MaxVal	 *//*									 *//*************************************************************************/    ResetFreq(MaxVal)/*  ---------  */    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(BaseInfo, UnknFrac, MaxVal, TotalItems)/*    -----------  */    float BaseInfo, UnknFrac;    DiscrValue MaxVal;    ItemCount TotalItems;{    DiscrValue v;    float ThisInfo=0.0, ThisGain, TotalInfo();    short ReasonableSubsets=0;    /*  Check whether all values are unknown or the same  */    if ( ! TotalItems ) return -Epsilon;    /*  There must be at least two subsets with MINOBJS items  */    ForEach(v, 1, MaxVal)    {	if ( ValFreq[v] >= MINOBJS ) ReasonableSubsets++;    }    if ( ReasonableSubsets < 2 ) return -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(V, MinVal, MaxVal)/*    ---------  */    ItemCount V[];    DiscrValue MinVal, MaxVal;{    DiscrValue v;    float Sum=0.0;    ItemCount N, TotalItems=0;    ForEach(v, MinVal, MaxVal)    {	N = V[v];	Sum += N * Log(N);	TotalItems += N;    }    return TotalItems * Log(TotalItems) - Sum;}/*************************************************************************//*									 *//*	Print distribution table for given attribute			 *//*									 *//*************************************************************************/    PrintDistribution(Att, MaxVal, ShowNames)/*  -----------------  */    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");    }}

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