get_default_training_options: Get default training options

In MOFA2: Multi-Omics Factor Analysis v2

Description

Function to obtain the default training options.

Usage

get_default_training_options(object)

Arguments

object

an untrained MOFA

Details

This function provides a default set of training options that can be modified and passed to the MOFA object in the prepare_mofa step (see example), i.e. after creating a MOFA object (using create_mofa) and before starting the training (using run_mofa) The training options are the following:

• maxiter: numeric value indicating the maximum number of iterations. Default is 1000. Convergence is assessed using the ELBO statistic.

• drop_factor_threshold: numeric indicating the threshold on fraction of variance explained to consider a factor inactive and drop it from the model. For example, a value of 0.01 implies that factors explaining less than 1% of variance (in each view) will be dropped. Default is -1 (no dropping of factors)

• convergence_mode: character indicating the convergence criteria, either "slow", "medium" or "fast", corresponding to 5e-7%, 5e-6% or 5e-5% deltaELBO change w.r.t. to the ELBO at the first iteration.

• verbose: logical indicating whether to generate a verbose output.

• startELBO: integer indicating the first iteration to compute the ELBO (default is 1).

• freqELBO: integer indicating the first iteration to compute the ELBO (default is 1).

• stochastic: logical indicating whether to use stochastic variational inference (only required for very big data sets, default is FALSE).

• gpu_mode: logical indicating whether to use GPUs (see details).

• seed: numeric indicating the seed for reproducibility (default is 42).

Value

Returns a list with default training options

Examples

# Using an existing simulated data with two groups and two views
file <- system.file("extdata", "test_data.RData", package = "MOFA2")

# Load data dt (in data.frame format)
load(file) 

# Create the MOFA object
MOFAmodel <- create_mofa(dt)

# Load default training options
train_opts <- get_default_training_options(MOFAmodel)

# Edit some of the training options
train_opts$convergence_mode <- "medium"
train_opts$startELBO <- 100
train_opts$seed <- 42

# Prepare the MOFA object
MOFAmodel <- prepare_mofa(MOFAmodel, training_options = train_opts)

MOFA2 documentation built on Nov. 8, 2020, 7:28 p.m.