Predict with keras

Usage

predict_keras(
  modelNN,
  predInput,
  maskNA = NULL,
  scaleInput = FALSE,
  col_means_train,
  col_stddevs_train,
  batch_size = NULL,
  filename = "",
  tempdirRaster = NULL,
  nCoresRaster = 2
)

Arguments

modelNN: an keras::keras() model.
predInput: data.frame or raster with colnames or layer names matching the expected input for modelRF.
maskNA: value to assign to NAs after scaling and passed to keras::layer_masking().
scaleInput: if TRUE, scale predInput with col_means_train and col col_stddevs_train.
col_means_train: the original mean of the predInput columns.
col_stddevs_train: the original sd of the predInput columns.
batch_size: for fit and predict functions. The bigger the better if it fits your available memory. Integer or "all".
filename: the file to write the raster predictions.
tempdirRaster: path to a directory to save temporal raster files.
nCoresRaster: number of cores used for parallelized raster cores. Use half of the available cores by default.