keras: what is the difference between model.predict and model.predict_proba

Question

I found model.predict and model.predict_proba both give an identical 2D matrix representing probabilities at each categories for each row.

Wha

Answer 1

predict

predict(self, x, batch_size=32, verbose=0)

Generates output predictions for the input samples, processing the samples in a batched way.

Arguments

x: the input data, as a Numpy array.
batch_size: integer.
verbose: verbosity mode, 0 or 1.

Returns

A Numpy array of predictions.

predict_proba

predict_proba(self, x, batch_size=32, verbose=1)

Generates class probability predictions for the input samples batch by batch.

Arguments

x: input data, as a Numpy array or list of Numpy arrays (if the model has multiple inputs).
batch_size: integer.
verbose: verbosity mode, 0 or 1.

Returns

A Numpy array of probability predictions.

Edit: In the recent version of keras, predict and predict_proba is same i.e. both give probabilities. To get the class labels use predict_classes. The documentation is not updated. (adapted from Avijit Dasgupta's comment)