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

Description Usage Arguments Examples

View source: R/CovNN2.R

Description

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

Usage

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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

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

## End(Not run)

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