runAutoencoderAssessment: Assessment of Neural Network Set Up

In kueckelj/SPATA2: A Toolbox for Spatial Gene Expression Analysis

Assessment of Neural Network Set Up

Description

Assesses different neural network set ups regarding the activation function and the number of bottleneck neurons.

Usage

assessAutoencoderOptions(
  expr_mtr,
  activations,
  bottlenecks,
  layers = c(128, 64, 32),
  dropout = 0.1,
  epochs = 20,
  verbose = TRUE
)

runAutoencoderAssessment(
  object,
  activations,
  bottlenecks,
  layers = c(128, 64, 32),
  dropout = 0.1,
  epochs = 20,
  verbose = TRUE
)

Arguments

expr_mtr	The expression matrix that is to be used as input for the neural network.
activations	Character vector. Denotes the activation functions to be assessed.
bottlenecks	Numeric vector. Denotes the different numbers of bottleneck neurons to be assessed.
layers	Numeric vector of length 3. Denotes the number of neurons in the three hidden layers. (default = c(128, 64, 32))
dropout	Numeric value. Denotes the dropout. (defaults to 0.1)
epochs	Numeric value. Denotes the epochs of the neural network. (defaults to 20)
object	A valid spata-object.

Value

• runAutoencoderAssessment(): The spata object containing the list that holds the total variance measured by irlba::prcomp_irlba() after each combination of activations/bottlenecks as well as the additional set up.

• assessAutoencoderOptions(): The list that holds the total variance measured by irlba::prcomp_irlba() after each combination of activations/bottlenecks as well as the additional set up.

kueckelj/SPATA2 documentation built on March 16, 2024, 10:25 a.m.