516c2a4c7e8f92e1ea299e966215c2ffe4c5b980,cifar10.py,,,#,14

Before Change

scores = model.evaluate_generator(test_generator.flow(testX, testY, nb_epoch), testX.shape[0])
print("Accuracy = %f" % (100 * scores[1]))
print("Error = %f" % (100 - 100 * scores[1]))

After Change

//                    validation_data=(testX, Y_test),
//                    nb_val_samples=testX.shape[0], verbose=2)

yPreds = model.predict(testX)
yPred = np.argmax(yPreds, axis=1)
yTrue = testY

accuracy = metrics.accuracy_score(yTrue, yPred) * 100
error = 100 - accuracy
print("Accuracy : ", accuracy)
print("Error : ", error)

Instances