
if __name__ == '__main__':
train_x,train_y,test_x,test_y = createDataSet()
y_test_pred = kNN_classify(50, 'E',train_x,train_y,test_x)
q=p=0
for i in range(0,(test_x.shape[0])):
if y_test_pred[i]==test_y[i]: #如果计算的结果和数据集里的诊断结果一致,q+1,否则p+1,
q=q+1
else:
p=p+1
q=(q/(test_x.shape[0]))*100
p=(p/(test_x.shape[0]))*100
print("{:.2f}%符合,{:.2f}%不符合".format(q,p))
#这个是用jupyter notebook 写的


