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I am using Keras to create a CNN model, and I would to use K-fold cross-validation to train the dataset.

The dataset contains images and I am using flow_from_directory function.

Do you have any idea how to use K-fold cross-validation in Keras to create a CNN model??

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  • $\begingroup$ Very expensive, this is why we use a validation set. $\endgroup$ Sep 24 '18 at 6:33
  • $\begingroup$ Do you mean Cross-validation method is very expensive? $\endgroup$
    – N.IT
    Sep 24 '18 at 12:09
  • $\begingroup$ Yes cross validation is considered expensive for dnn , because you have to do the training , testing k times $\endgroup$ Sep 24 '18 at 14:52
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    $\begingroup$ I want to do cross validation, even if it is expensive $\endgroup$
    – N.IT
    Oct 2 '18 at 5:02
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It is very common to use sklearn for cross validation.

The most known methods are KFold and cross_val_score imported from sklearn.model_selection.

You can then use tf.keras.wrappers.scikit_learn.KerasClassifier to implement the scikit-learn classifier with Keras model.

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