Index

A

auto_stdnorm (bob.learn.mlp.DataShuffler attribute)

B

BackProp (class in bob.learn.mlp) backward_step() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) batch_size (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute) bias_deltas (bob.learn.mlp.RProp attribute)

bias_derivatives (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute) biases (bob.learn.mlp.Machine attribute) bob.learn.mlp (module)

C

Cost (class in bob.learn.mlp) cost() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) cost_object (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute)

CrossEntropyLoss (class in bob.learn.mlp) cxx (C++ member), [1], [2], [3], [4], [5]

D

data_width (bob.learn.mlp.DataShuffler attribute) DataShuffler (class in bob.learn.mlp) delta_max (bob.learn.mlp.RProp attribute) delta_min (bob.learn.mlp.RProp attribute)

delta_zero (bob.learn.mlp.RProp attribute) deltas (bob.learn.mlp.RProp attribute) derivatives (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute) draw() (bob.learn.mlp.DataShuffler method)

E

error (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute) error() (bob.learn.mlp.Cost method) (bob.learn.mlp.CrossEntropyLoss method) (bob.learn.mlp.SquareError method)

eta_minus (bob.learn.mlp.RProp attribute) eta_plus (bob.learn.mlp.RProp attribute)

F

f() (bob.learn.mlp.Cost method) (bob.learn.mlp.CrossEntropyLoss method) (bob.learn.mlp.SquareError method) f_prime() (bob.learn.mlp.Cost method) (bob.learn.mlp.CrossEntropyLoss method) (bob.learn.mlp.SquareError method)

forward() (bob.learn.mlp.Machine method) forward_step() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method)

G

get_config() (in module bob.learn.mlp)

H

hidden_activation (bob.learn.mlp.Machine attribute)

hidden_layers() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method)

I

initialize() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) input_divide (bob.learn.mlp.Machine attribute) input_subtract (bob.learn.mlp.Machine attribute)

is_compatible() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) is_similar_to() (bob.learn.mlp.Machine method)

L

learning_rate (bob.learn.mlp.BackProp attribute) load() (bob.learn.mlp.Machine method)

logistic_activation (bob.learn.mlp.CrossEntropyLoss attribute)

M

Machine (class in bob.learn.mlp)

momentum (bob.learn.mlp.BackProp attribute)

N

number_of_parameters() (in module bob.learn.mlp)

O

output (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute)

output_activation (bob.learn.mlp.Machine attribute)

P

parent (C++ member), [1] previous_bias_derivatives (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) previous_derivatives (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) PyBobLearnBackProp_Check (C++ function) PyBobLearnBackPropObject (C++ type) PyBobLearnCost_Check (C++ function) PyBobLearnCost_NewFromCost (C++ function) PyBobLearnCostObject (C++ type)

PyBobLearnDataShuffler_Check (C++ function) PyBobLearnDataShufflerObject (C++ type) PyBobLearnMLPMachine_Check (C++ function) PyBobLearnMLPMachineObject (C++ type) PyBobLearnMLPTrainer_Check (C++ function) PyBobLearnMLPTrainerObject (C++ type) PyBobLearnRProp_Check (C++ function) PyBobLearnRPropObject (C++ type)

R

randomize() (bob.learn.mlp.Machine method) reset() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method)

roll() (in module bob.learn.mlp) RProp (class in bob.learn.mlp)

S

save() (bob.learn.mlp.Machine method) set_bias_delta() (bob.learn.mlp.RProp method) set_bias_derivative() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) set_delta() (bob.learn.mlp.RProp method) set_derivative() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) set_error() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method)

set_output() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) (bob.learn.mlp.Trainer method) set_previous_bias_derivative() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) set_previous_derivative() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method) shape (bob.learn.mlp.Machine attribute) SquareError (class in bob.learn.mlp) stdnorm() (bob.learn.mlp.DataShuffler method)

T

target_width (bob.learn.mlp.DataShuffler attribute) train() (bob.learn.mlp.BackProp method) (bob.learn.mlp.RProp method)

train_biases (bob.learn.mlp.BackProp attribute) (bob.learn.mlp.RProp attribute) (bob.learn.mlp.Trainer attribute) Trainer (class in bob.learn.mlp)

U

unroll() (in module bob.learn.mlp)

W

weights (bob.learn.mlp.Machine attribute)