def createConfMatrix(self, iterations = 100):
if iterations > len(self.df):
raise Exception('More iterations than data')
dim = self.answer.max()
cm = ConfusionMatrix(dim)
for i in range(iterations):
# copy original data
df = self.df
ans = self.answer
# select data
item = df.loc[i]
real = ans.loc[i]
# remove data
self.df = self.df.drop(i, axis = 0)
self.answer = self.answer.drop(i)
# get knn
predict = self.getKNN(item)
# check validation
cm.validate(predict, real)
# restore data
self.df = df
self.answer = ans
print('loading: {}/{}'.format(i+1, iterations))
print('')
cm.showMatrix()
print("Erro: ",cm.totalError(iterations))
