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double svm_predict_probability( | |
const svm_model *model, const svm_node *x, double *prob_estimates) | |
{ | |
if ((model->param.svm_type == C_SVC || model->param.svm_type == NU_SVC) && | |
model->probA!=NULL && model->probB!=NULL) | |
{ | |
int i; | |
int nr_class = model->nr_class; | |
double *dec_values = Malloc(double, nr_class*(nr_class-1)/2); | |
svm_predict_values(model, x, dec_values); | |
double min_prob=1e-7; | |
double **pairwise_prob=Malloc(double *,nr_class); | |
for(i=0;i<nr_class;i++) | |
pairwise_prob[i]=Malloc(double,nr_class); | |
int k=0; | |
for(i=0;i<nr_class;i++) | |
for(int j=i+1;j<nr_class;j++) | |
{ | |
pairwise_prob[i][j]=min(max(sigmoid_predict(dec_values[k],model->probA[k],model->probB[k]),min_prob),1-min_prob); | |
pairwise_prob[j][i]=1-pairwise_prob[i][j]; | |
k++; | |
} | |
multiclass_probability(nr_class,pairwise_prob,prob_estimates); | |
int prob_max_idx = 0; | |
for(i=1;i<nr_class;i++) | |
if(prob_estimates[i] > prob_estimates[prob_max_idx]) | |
prob_max_idx = i; | |
for(i=0;i<nr_class;i++) | |
free(pairwise_prob[i]); | |
free(dec_values); | |
free(pairwise_prob); | |
return model->label[prob_max_idx]; | |
} | |
else | |
return svm_predict(model, x); | |
} |
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