Index

_

__call__() (jenn.core.optimization.Backtracking method) (jenn.core.optimization.LineSearch method) (jenn.core.optimization.Update method)

A

Activation (class in jenn.core.activation) actual_by_predicted() (in module jenn.utils.plot) ADAM (class in jenn.core.optimization)

ADAMOptimizer (class in jenn.core.optimization) avg() (in module jenn.core.data) avg_x (jenn.core.data.Dataset property) avg_y (jenn.core.data.Dataset property)

B

Backtracking (class in jenn.core.optimization)

C

Cache (class in jenn.core.cache) contours() (in module jenn.utils.plot)

convergence() (in module jenn.utils.plot) Cost (class in jenn.core.cost)

D

Dataset (class in jenn.core.data)

denormalize() (in module jenn.core.data) denormalize_partials() (in module jenn.core.data)

E

evaluate() (jenn.core.activation.Activation class method) (jenn.core.activation.Linear class method) (jenn.core.activation.Relu class method) (jenn.core.activation.Tanh class method) (jenn.core.cost.Cost method) (jenn.core.cost.GradientEnhancement method) (jenn.core.cost.Regularization method) (jenn.core.cost.SquaredLoss method) (jenn.model.NeuralNet method) (jenn.synthetic.Linear class method) (jenn.synthetic.Parabola class method) (jenn.synthetic.Rastrigin class method) (jenn.synthetic.Rosenbrock class method) (jenn.synthetic.Sinusoid class method) (jenn.synthetic.TestFunction method)

eye() (in module jenn.core.propagation)

F

first_derivative() (jenn.core.activation.Activation class method) (jenn.core.activation.Linear class method) (jenn.core.activation.Relu class method) (jenn.core.activation.Tanh class method) (jenn.synthetic.Linear class method) (jenn.synthetic.Parabola class method) (jenn.synthetic.Rastrigin class method) (jenn.synthetic.Rosenbrock class method) (jenn.synthetic.Sinusoid class method) (jenn.synthetic.TestFunction method)

first_derivative_FD() (jenn.synthetic.TestFunction class method) first_layer_forward() (in module jenn.core.propagation) first_layer_partials() (in module jenn.core.propagation) fit() (jenn.model.NeuralNet method)

G

GD (class in jenn.core.optimization) GDOptimizer (class in jenn.core.optimization)

goodness_of_fit() (in module jenn.utils.plot) gradient_enhancement() (in module jenn.core.propagation) GradientEnhancement (class in jenn.core.cost)

I

initialize() (jenn.core.parameters.Parameters method)

J

jenn.core.activation module jenn.core.cache module jenn.core.cost module jenn.core.data module jenn.core.optimization module jenn.core.parameters module

jenn.core.propagation module jenn.core.training module jenn.model module jenn.synthetic module jenn.utils.metrics module jenn.utils.plot module

L

L (jenn.core.parameters.Parameters property) last_layer_backward() (in module jenn.core.propagation) layers (jenn.core.parameters.Parameters property) Linear (class in jenn.core.activation) (class in jenn.synthetic)

LineSearch (class in jenn.core.optimization) load() (jenn.core.parameters.Parameters method) (jenn.model.NeuralNet method)

M

m (jenn.core.cache.Cache property) (jenn.core.data.Dataset property) mini_batches() (in module jenn.core.data) (jenn.core.data.Dataset method) minimize() (jenn.core.optimization.Optimizer method) model_backward() (in module jenn.core.propagation) model_forward() (in module jenn.core.propagation) model_partials_forward() (in module jenn.core.propagation) module jenn.core.activation jenn.core.cache jenn.core.cost jenn.core.data jenn.core.optimization jenn.core.parameters jenn.core.propagation jenn.core.training jenn.model jenn.synthetic jenn.utils.metrics jenn.utils.plot

N

n_x (jenn.core.cache.Cache property) (jenn.core.data.Dataset property) (jenn.core.parameters.Parameters property) n_y (jenn.core.cache.Cache property) (jenn.core.data.Dataset property) (jenn.core.parameters.Parameters property)

NeuralNet (class in jenn.model) next_layer_backward() (in module jenn.core.propagation) next_layer_forward() (in module jenn.core.propagation) next_layer_partials() (in module jenn.core.propagation) normalize() (in module jenn.core.data) (jenn.core.data.Dataset method) normalize_partials() (in module jenn.core.data)

O

objective_function() (in module jenn.core.training)

objective_gradient() (in module jenn.core.training) Optimizer (class in jenn.core.optimization)

P

Parabola (class in jenn.synthetic) Parameters (class in jenn.core.parameters) partials (jenn.core.parameters.Parameters property)

partials_forward() (in module jenn.core.propagation) predict() (jenn.model.NeuralNet method) predict_partials() (jenn.model.NeuralNet method)

R

r_square() (in module jenn.utils.metrics) Rastrigin (class in jenn.synthetic) Regularization (class in jenn.core.cost)

Relu (class in jenn.core.activation) residuals_by_predicted() (in module jenn.utils.plot) Rosenbrock (class in jenn.synthetic)

S

sample() (jenn.synthetic.Linear class method) (jenn.synthetic.Parabola class method) (jenn.synthetic.Rastrigin class method) (jenn.synthetic.Rosenbrock class method) (jenn.synthetic.Sinusoid class method) (jenn.synthetic.TestFunction class method) save() (jenn.core.parameters.Parameters method) (jenn.model.NeuralNet method) second_derivative() (jenn.core.activation.Activation class method) (jenn.core.activation.Linear class method) (jenn.core.activation.Relu class method) (jenn.core.activation.Tanh class method)

sensitivity_profile() (in module jenn.utils.plot) sensitivity_profiles() (in module jenn.utils.plot) set_weights() (jenn.core.data.Dataset method) Sinusoid (class in jenn.synthetic) SquaredLoss (class in jenn.core.cost) stack() (jenn.core.parameters.Parameters method) stack_partials() (jenn.core.parameters.Parameters method) stack_partials_per_layer() (jenn.core.parameters.Parameters method) stack_per_layer() (jenn.core.parameters.Parameters method) std() (in module jenn.core.data) std_x (jenn.core.data.Dataset property) std_y (jenn.core.data.Dataset property)

T

Tanh (class in jenn.core.activation)

TestFunction (class in jenn.synthetic) train_model() (in module jenn.core.training)

U

unstack() (jenn.core.parameters.Parameters method)

unstack_partials() (jenn.core.parameters.Parameters method) Update (class in jenn.core.optimization)