from IPython.display import display
#print( df["topic"].factorize().CategoricalIndex)
#df["topic"].factorize()
for predicted in df["topic"].factorize()[0]:
for actual in df["topic"].factorize()[0]:
if predicted != actual and conf_mat[actual, predicted] >= 10:
print("'{}' predicted as '{}' : {} examples.".format(topics[actual],topics[predicted], conf_mat[actual, predicted]))
display(df.loc[indices_test[(y_test == actual) & (pred == predicted)]][['topic', 'body_wakati']])
print('')
我想通过遍历数据帧中的所有数据来从混淆矩阵中看到错误的分类,但是它一遍又一遍地产生相同的数据,代码是否有问题?
这是df数据和索引测试