SVM.c

#include "ELM.h"

#ifdef SVM

#include "svm.h"
#include <stdio.h>
#include <stdbool.h>


#ifdef REGRESSION
float (*pRegress)(float X[]) = svm_regression;
#else
int (*pClassf)(float X[]) = svm_classification;
#endif


float *PCA_transform(float *);




#ifndef REGRESSION
int svm_classification(float X[])
{
    int m;
    if (N_CLASS == 2)
    {
        float y = bias[0];
        int k;
        for (k = 0; k < N_FEATURE; k++)
        {
            y += support_vectors[0][k] * X[k];
        }
        if (y < 0)
        {
            return 0;
        }
        else
        {
            return 1;
        }
    }
    else
    {
//         float bestDistance = -1000000;
//         for (m = 0; m < N_CLASS; m++)
//         {
//             float y = bias[m];
//             int k;
//             for (k = 0; k < N_FEATURE; k++)
//             {
//                 y += support_vectors[m][k] * X[k];
//             }
//             if (y > bestDistance)
//             {
//                 bestDistance = y;
//                 return m;
//             }
//         }
	    float dot[WEIGTH_DIM];
	    int out[WEIGTH_DIM];
	    int prediction;
	    for (int i = 0; i < WEIGTH_DIM; i++)
	    {
		float distance = 0;
		dot[i] = bias[i];
		for (int k = 0; k < N_FEATURE; k++)
		{
		    dot[i] += X[k] * support_vectors[i][k];
		}
		if(dot[i] > 0)
		{
		    out[i] = 0;
		}
		else
		{
		    out[i] = 1; 
		}
	    }

	    for(int i = 0; i < WEIGTH_DIM; i++)
	    {
		out[i] = Truth_Table[out[i]][i];
	    }

	    // find the most frequent class
	    int max_count = 0;
	    for(int i = 0; i < N_CLASS; i++)
	    {
		int count = 0;
		for(int j = 0; j < WEIGTH_DIM; j++)
		{
		    if(out[j] == i)
		    {
			count++;
		    }
		}
		if(count > max_count)
		{
		    max_count = count;
		    prediction = i;
		}
	    }
	    return prediction; 
    }
}
#endif

#ifdef REGRESSION
float svm_regression(float X[])
{
    float y = bias[0];
    int k;
    for (k = 0; k < N_FEATURE; k++)
    {
        y += support_vectors[0][k] * X[k];
    }

    /*
    #ifdef MINMAX_SCALING
        y = y / S_Y;
    #elif defined (STANDARD_SCALING)
        y = y * S_Y + U_Y;
    #endif
	*/
    return y;
}
#endif

#endif