#!/usr/bin/env pythonimport randomfrom svm import *def do_cross_validation(prob_x, prob_y, param, nr_fold):	"Do cross validation for a given SVM problem."	prob_l = len(prob_y)	total_correct = 0	total_error = sumv = sumy = sumvv = sumyy = sumvy = 0.	prob = svm_problem(prob_y, prob_x)    	target = cross_validation(prob, param, nr_fold)	for i in range(prob_l):		if param.svm_type == EPSILON_SVR or param.svm_type == NU_SVR:			v = target[i]			y = prob_y[i]			sumv = sumv + v			sumy = sumy + y			sumvv = sumvv + v * v			sumyy = sumyy + y * y			sumvy = sumvy + v * y			total_error = total_error + (v-y) * (v-y)		else:			v = target[i]			if v == prob_y[i]:				total_correct = total_correct + 1 	if param.svm_type == EPSILON_SVR or param.svm_type == NU_SVR:		print "Cross Validation Mean squared error = %g" % (total_error / prob_l)		print "Cross Validation Squared correlation coefficient = %g" % (((prob_l * sumvy - sumv * sumy) * (prob_l * sumvy - sumv * sumy)) / ((prob_l * sumvv - sumv * sumv) * (prob_l * sumyy - sumy * sumy)))	else:		print "Cross Validation Accuracy = %g%%" % (100.0 * total_correct / prob_l)