Error predicting

[prem1215]

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ValueError Traceback (most recent call last)

in 8 labelencoder = joblib.load(label_encoder_file_name) 9 for label in reversed(np.argsort(y_output)[0,-5:]): ---> 10 print(str(round(y_output[0,label]*100,2)).zfill(5), "% ",labelencoder.inverse_transform(label)) ~\Anaconda3\envs\VQA1\lib\site-packages\sklearn\preprocessing\label.py in inverse_transform(self, y) 271 """ 272 check_is_fitted(self, 'classes_') --> 273 y = column_or_1d(y, warn=True) 274 # inverse transform of empty array is empty array 275 if _num_samples(y) == 0: ~\Anaconda3\envs\VQA1\lib\site-packages\sklearn\utils\validation.py in column_or_1d(y, warn) 795 return np.ravel(y) 796 --> 797 raise ValueError("bad input shape {0}".format(shape)) 798 799 ValueError: bad input shape ()

[WeiYangBin]

I have solved the problem, we only need:

print("{} % {}!".format(round(y_output[0,label]*100,2), labelencoder.inverse_transform([label])[0]))

Because the inverse transform requires that we pass in an array

[jiteshm17]

@WeiYangBin thank you so much for this. However, one thing to note is that this only works if the scikit-learn version is 0.21.1