CODEWITHSUNDEEP
pythontensorflowkerasdeep-learning
Diana
Diana

Reputation: 27

ValueError: The model is not configured to compute accuracy. You should pass `metrics=["accuracy"]` to the `model.compile()` method

I am very new in Deep Learning: I am doing a deep learning course on Udemy. once I execute my code, it says:

ValueError: The model is not configured to compute accuracy. You should pass metrics=["accuracy"] to the model.compile() method.

I tried to change 'accuracy' into 'acc', It gives me no more error, but the code is super fast, it shows me only 10 epochs instead of 100. besides I was expecting accuracy around 83% but I am having something like 79%.

can someone please help me?

''''

import keras
from keras.wrappers.scikit_learn import KerasClassifier
from sklearn.model_selection import cross_val_score
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense

def build_classifier():
    classifier = Sequential()
    classifier.add(Dense(6, kernel_initializer='uniform', activation='relu', input_dim= 11))
    classifier.add(Dense(6, kernel_initializer='uniform', activation='relu'))
    classifier.add(Dense(1, kernel_initializer='uniform', activation='sigmoid'))
    classifier.compile(optimizer = 'adam', loss = 'binary_crossentropy', metrics = ['accuracy'])
    return classifier

classifier = KerasClassifier(build_fn= build_classifier, batch_size=10 , nb_epoch=100)
accuracies = cross_val_score(estimator = classifier, X = x_train, y = y_train, cv=10, n_jobs=-1)

'''' This is my fulltraceback:

''''

accuracies = cross_val_score(estimator = classifier, X = x_train, y = y_train, cv=10, n_jobs=-1, verbose=0)
Traceback (most recent call last):

  File "<ipython-input-138-36c63e93365e>", line 1, in <module>
    accuracies = cross_val_score(estimator = classifier, X = x_train, y = y_train, cv=10, n_jobs=-1, verbose=0)

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\site-packages\sklearn\model_selection\_validation.py", line 389, in cross_val_score
    error_score=error_score)

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\site-packages\sklearn\model_selection\_validation.py", line 235, in cross_validate
    for train, test in cv.split(X, y, groups))

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\site-packages\joblib\parallel.py", line 1017, in __call__
    self.retrieve()

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\site-packages\joblib\parallel.py", line 909, in retrieve
    self._output.extend(job.get(timeout=self.timeout))

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\site-packages\joblib\_parallel_backends.py", line 562, in wrap_future_result
    return future.result(timeout=timeout)

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\concurrent\futures\_base.py", line 435, in result
    return self.__get_result()

  File "C:\ProgramData\Anaconda3\envs\deeplearning\lib\concurrent\futures\_base.py", line 384, in __get_result
    raise self._exception

ValueError: The model is not configured to compute accuracy. You should pass `metrics=["accuracy"]` to the `model.compile()` method.
''''

I also tried this: '

try:

    accuracies = cross_val_score(estimator = classifier, X = x_train, y = y_train, cv=10, n_jobs=-1, verbose=0)
except ValueError as e:
    print ("ValueError:", e)
ValueError: The model is not configured to compute accuracy. You should pass `metrics=["accuracy"]` to the `model.compile()` method.

'

Upvotes: 1

Views: 322

Answers (1)

Dr. Snoopy
Dr. Snoopy

Reputation: 56347

In your imports you are mixing imports between the keras and tf.keras packages, that is actually not supported, you should choose one and make all imports from the selected package.

Upvotes: 1

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