populate.nn: Build a population of Neural Nets

In coldfir3/neatr: NeuroEvolution of Augmenting Topologies

Description

This function generates a population of neural nets with the same input-output configuration

Usage

populate.nn(npop, inputs, outputs, hiddens = 0, weights = NULL,
  weight_range = c(-1, 1), enable_rate = 0.7)

Arguments

npop	Numerical value of the number of individuals of the population
inputs	Numeric indicating the number of inputs and outputs
outputs	Numeric indicating the number of inputs and outputs
hiddens	Numeric Vector indicating the number of hidden neurons per layer (optional)
weights	Numeric Vector of the nodal weight, if NULL (default) random weights will be sampled from an uniform distribution over weight_range. missing values will be randomized and excess values will be cropped
weight_range	Numeric Vector of length 2 with the lower and upper bounds for the random weight generation
enable_rate	Numeric between 0 and 1 indicating the probability that a link will be enabled

Examples

populate.nn(10, 3, 1)
populate.nn(100, 3, 1)

coldfir3/neatr documentation built on May 23, 2019, 4:24 p.m.