dewlap_neural: Habitat classification with neural networks

Description Usage Arguments Value Author(s)

View source: R/dewlap_neural.R

Description

This function trains neural networks to recognize differences between habitats. Each neural network is trained on a random sample of half of the data, and tested against the other half. The success of the classification is compared to a null expectation generated from a permuted dataset where no differences exist between habitats. The 5% best performing machines are studied more in depth to identify what were the most important variables in discriminating between habitats.

Usage

1
dewlap_neural(specdata, vars, nRepet = 1000, seed)

Arguments

specdata

A data frame containing at least columns for the dependent variables, as well as a column "habitat".

vars

A character or integer vector. The names, or indices, of the dependent variables in specdata.

nRepet

The number of neural networks to train (same number for empirical and permuted datasets).

seed

Seed for random number gnerators

Value

A list of two data frames: one contains success and p-values for randomized and empirical data, the other contains the importance variables in the 5% best classifiers.

Author(s)

Raphael Scherrer


rscherrer/sagreicolor documentation built on Dec. 26, 2018, 1:15 p.m.