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hub / github.com/MichalDanielDobrzanski/DeepLearningPython / SGD

Method SGD

network2.py:129–215  ·  view source on GitHub ↗

Train the neural network using mini-batch stochastic gradient descent. The ``training_data`` is a list of tuples ``(x, y)`` representing the training inputs and the desired outputs. The other non-optional parameters are self-explanatory, as is the regularization

(self, training_data, epochs, mini_batch_size, eta,
            lmbda = 0.0,
            evaluation_data=None,
            monitor_evaluation_cost=False,
            monitor_evaluation_accuracy=False,
            monitor_training_cost=False,
            monitor_training_accuracy=False,
            early_stopping_n = 0)

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Callers

nothing calls this directly

Calls 3

update_mini_batchMethod · 0.95
total_costMethod · 0.95
accuracyMethod · 0.95

Tested by

no test coverage detected