setCovNN2: Create setting for CovNN2 model - convolution across input...

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

Description

Create setting for CovNN2 model - convolution across input and time - https://arxiv.org/pdf/1608.00647.pdf

Usage

setCovNN2(
  batchSize = 1000,
  outcomeWeight = 1,
  lr = 1e-05,
  decay = 1e-06,
  dropout = 0,
  epochs = 10,
  filters = 3,
  kernelSize = 10,
  loss = "binary_crossentropy",
  seed = NULL
)

Arguments

batchSize	The number of samples to used in each batch during model training
outcomeWeight	The weight assined to the outcome (make greater than 1 to reduce unballanced label issue)
lr	The learning rate
decay	The decay of the learning rate
dropout	[currently not used] the dropout rate for regularisation
epochs	The number of times data is used to train the model (e.g., epoches=1 means data only used once to train)
filters	The number of columns output by each convolution
kernelSize	The number of time dimensions used for each convolution
loss	The loss function implemented
seed	The random seed

Examples

## Not run: 
model.CovNN <- setCovNN()

## End(Not run)

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