bob.learn.mlp
2.1.6
Multi-Layer Perceptron (MLP) Machines and Trainers
Python API
C++ API
bob.learn.mlp
Docs
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Index
Index
A
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B
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C
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D
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E
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F
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G
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H
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I
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L
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M
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N
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O
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P
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R
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S
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T
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U
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W
A
auto_stdnorm (bob.learn.mlp.DataShuffler attribute)
B
BackProp (class in bob.learn.mlp)
backward_step() (bob.learn.mlp.Trainer method)
batch_size (bob.learn.mlp.Trainer attribute)
bias_deltas (bob.learn.mlp.RProp attribute)
bias_derivatives (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.Trainer method)
cost_object (bob.learn.mlp.Trainer attribute)
CrossEntropyLoss (class in bob.learn.mlp)
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.Trainer attribute)
draw() (bob.learn.mlp.DataShuffler method)
E
error (bob.learn.mlp.Trainer attribute)
error() (bob.learn.mlp.Cost method)
eta_minus (bob.learn.mlp.RProp attribute)
eta_plus (bob.learn.mlp.RProp attribute)
F
f() (bob.learn.mlp.Cost method)
f_prime() (bob.learn.mlp.Cost method)
forward() (bob.learn.mlp.Machine method)
forward_step() (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.Trainer method)
I
initialize() (bob.learn.mlp.Trainer method)
input_divide (bob.learn.mlp.Machine attribute)
input_subtract (bob.learn.mlp.Machine attribute)
is_compatible() (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.Trainer attribute)
output_activation (bob.learn.mlp.Machine attribute)
P
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)
PyBobLearnBackPropObject::cxx (C++ member)
PyBobLearnBackPropObject::parent (C++ member)
PyBobLearnCost_Check (C++ function)
PyBobLearnCost_NewFromCost (C++ function)
PyBobLearnCostObject (C++ type)
PyBobLearnCostObject::cxx (C++ member)
PyBobLearnDataShuffler_Check (C++ function)
PyBobLearnDataShufflerObject (C++ type)
PyBobLearnDataShufflerObject::cxx (C++ member)
PyBobLearnMLPMachine_Check (C++ function)
PyBobLearnMLPMachineObject (C++ type)
PyBobLearnMLPMachineObject::cxx (C++ member)
PyBobLearnMLPTrainer_Check (C++ function)
PyBobLearnMLPTrainerObject (C++ type)
PyBobLearnMLPTrainerObject::cxx (C++ member)
PyBobLearnRProp_Check (C++ function)
PyBobLearnRPropObject (C++ type)
PyBobLearnRPropObject::cxx (C++ member)
PyBobLearnRPropObject::parent (C++ member)
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.Trainer method)
set_delta() (bob.learn.mlp.RProp method)
set_derivative() (bob.learn.mlp.Trainer method)
set_error() (bob.learn.mlp.Trainer method)
set_output() (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.Trainer attribute)
Trainer (class in bob.learn.mlp)
U
unroll() (in module bob.learn.mlp)
W
weights (bob.learn.mlp.Machine attribute)