Predicting on Test Data

To predict the digits in an unseen data is very easy. You simply need to call the predict_classes method of the model by passing it to a vector consisting of your unknown data points.

predictions = model.predict_classes(X_test)

The method call returns the predictions in a vector that can be tested for 0’s and 1’s against the actual values. This is done using the following two statements −

correct_predictions = np.nonzero(predictions == y_test)[0]
incorrect_predictions = np.nonzero(predictions != y_test)[0]

Finally, we will print the count of correct and incorrect predictions using the following two program statements −

print(len(correct_predictions)," classified correctly")
print(len(incorrect_predictions)," classified incorrectly")

When you run the code, you will get the following output −

9837 classified correctly
163 classified incorrectly

Now, as you have satisfactorily trained the model, we will save it for future use.

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