Weights-class: Weights objects

In TeachNet: Fits Neural Networks to Learn About Backpropagation

Description

Contains the weights for a one hidden layer neural network in TeachNet the here cold "Arguments" are the slots in the S4 class Weights

Arguments

alpha	Intercept from output layer
alpha_h	Intercept from hidden layer
w_h	Weights from hidden layer to output layer
w_ih	Weights from input layer to hidden layer

Author(s)

Georg Steinbuss

See Also

Weights2-class

Examples

H <- 3 # number of neurons in hidden layer
I <- 6 # number of inputs

random_weights <- new("Weights", alpha = rnorm(1), alpha_h = rnorm(H), w_h = rnorm(H), 
                      w_ih = matrix(nrow=I,ncol=H, data=rnorm(I*H)))

TeachNet documentation built on May 2, 2019, 7 a.m.