I'm working in Keras/TensorFlow. This is my Keras model:

```
model = Sequential()
model.add(Dense(512, input_shape=(max_words,)))
model.add(Activation('relu'))
model.add(Dropout(0.5))
model.add(Dense(num_classes))
model.add(Activation('softmax'))
model.compile(loss='categorical_crossentropy',
optimizer='adam',
metrics=['accuracy'])
```

After training step and test step, I'm coding a method that take the input (which i don't know his class) e this method returns the class prediction with level of confidence. Now this method returns only the prediction of class. This is the method:

```
def predict(input):
try:
x_prediction = tokenize.texts_to_matrix(input)
q = model.predict(np.array([x_prediction[0],]))
predicted_label = text_labels[np.argmax(q)]
print("Prediction: " + predicted_label + "\n")
except:
return "Error"
```

What should I add in the method to get the confidence level of the respective prediction? I don't want use the confidence of variable 'q' but I want to use the Bayes Approach. How can I do? Thanks