autoPLIER.fit: AutoPLIER Fit Method

In Bishop-Laboratory/autoplieR: What the Package Does (One Line, Title Case)

AutoPLIER Fit Method

Description

Computes the mean and standard deviation for scaling of a created autoPLIER model.

Usage

autoPLIER.fit(ap, ...)

Arguments

ap	AutoPLIER object.
...	Additional arguments for autoPLIER.fit. See details.

Details

Additional arguments

• x_train - Training dataset used to train the model.

• pathways - Pathways dataset.

• callbacks - List of callbacks to apply during training.

• batch_size - Fixed batch size. Default: NULL.

• maxepoch - Max number of epochs. Default: 2000.

• verbose - Verbosity mode. 0 = silent, 1 = progress bar, 2 = one line per epoch. Default: 2.

• valfrac - Fraction of the training dataset used as validation data. Default: 0.3.

Value

A Python object called autoplier.model.autoPLIER that cannot be viewed.

Examples

# Example datasets
xtrain <- read.csv(system.file("extdata", "GSE157103_icu_tpm.csv.xz", package = "autoplieR"),
 row.names = 1)
pwy <- read.csv(system.file("extdata", "pathways.csv.xz", package = "autoplieR"),
 row.names = 1)

# Fit the model
mod <- autoPLIER(n_components = 50)
mod <- autoPLIER.fit(mod, x_train = xtrain, pathways = pwy, maxepoch=100L, verbose = 0)

Bishop-Laboratory/autoplieR documentation built on July 11, 2022, 4:49 a.m.