iucnn: Neural Network classifier to automate occurrence-based...

In barnabywalker/tidyassessments: Model Wrappers for Automated Conservation Assessments

Neural Network classifier to automate occurrence-based conservation assessments

Description

iucnn() defines a neural network for predicting the conservation status of species given species-level predictors calculated from occurrence records. This is an implementation of the IUCNN model so it works in the tidymodels framework.

Usage

iucnn(
  mode = "classification",
  engine = "keras",
  layers = NULL,
  dropout = NULL,
  epochs = NULL
)

Arguments

mode	A single character string for the prediction outcome mode. Only "classification" is allowed.
engine	A single character string specifying the engine to use.
layers	A string specification of the hidden units in each layer, e.g. "40_20" for a two-layer network with a 40-unit layer then a 20-unit layer.
dropout	A number between 0 (inclusive) and 1 denoting the proportion of model parameters randomly set to zero during model training.
epochs	An integer for the number of training iterations.

Details

Currently only the binary threatened/not threatened classification is implemented.

Examples

parsnip::show_engines("iucnn")

iucnn(layers="40_20", dropout=0.3, epochs=10)

barnabywalker/tidyassessments documentation built on April 8, 2022, 12:32 p.m.