setDeepNN: Create setting for DeepNN model

In hxia/plp-git-demo: Package for patient level prediction using data in the OMOP Common Data Model

Description

Create setting for DeepNN model

Usage

setDeepNN(
  units = list(c(128, 64), 128),
  layer_dropout = c(0.2),
  lr = c(1e-04),
  decay = c(1e-05),
  outcome_weight = c(1),
  batch_size = c(100),
  epochs = c(100),
  seed = NULL
)

Arguments

units	The number of units of the deep network - as a list of vectors
layer_dropout	The layer dropout rate (regularisation)
lr	Learning rate
decay	Learning rate decay over each update.
outcome_weight	The weight of the outcome class in the loss function
batch_size	The number of data points to use per training batch
epochs	Number of times to iterate over dataset
seed	Random seed used by deep learning model

Examples

## Not run: 
model <- setDeepNN()

## End(Not run)

hxia/plp-git-demo documentation built on March 19, 2021, 1:54 a.m.