Index

_

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

A

Activation (class in jenn.core.activation) 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)

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)

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

F

finite_difference() (in module jenn.utilities) 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)

first_layer_forward() (in module jenn.core.propagation) first_layer_partials() (in module jenn.core.propagation) fit() (jenn.core.model.NeuralNet method) (jenn.NeuralNet method) from_jmp() (in module jenn.utilities)

G

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

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

I

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

J

jenn module jenn.core.activation module jenn.core.cache module jenn.core.cost module jenn.core.data module jenn.core.model module

jenn.core.optimization module jenn.core.parameters module jenn.core.propagation module jenn.core.training module jenn.synthetic_data module jenn.utilities 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)

LineSearch (class in jenn.core.optimization) load() (jenn.core.model.NeuralNet class method) (jenn.core.parameters.Parameters class method) (jenn.NeuralNet class 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 jenn.core.activation jenn.core.cache jenn.core.cost jenn.core.data jenn.core.model jenn.core.optimization jenn.core.parameters jenn.core.propagation jenn.core.training jenn.synthetic_data jenn.utilities

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) (class in jenn.core.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

Parameters (class in jenn.core.parameters) partials (jenn.core.parameters.Parameters property) partials_forward() (in module jenn.core.propagation) plot_actual_by_predicted() (in module jenn) plot_contours() (in module jenn) plot_convergence() (in module jenn) plot_goodness_of_fit() (in module jenn)

plot_histogram() (in module jenn) plot_residual_by_predicted() (in module jenn) plot_sensitivity_profiles() (in module jenn) predict() (jenn.core.model.NeuralNet method) (jenn.NeuralNet method) predict_partials() (jenn.core.model.NeuralNet method) (jenn.NeuralNet method)

R

rbf() (in module jenn.utilities)

Regularization (class in jenn.core.cost) Relu (class in jenn.core.activation)

S

sample() (in module jenn.utilities) save() (jenn.core.model.NeuralNet method) (jenn.core.parameters.Parameters method) (jenn.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)

set_weights() (jenn.core.data.Dataset method) 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)

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)

V

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