train_Tucker: Train a Tucker model using BaTFLED algorthm

In BaTFLED3D: Bayesian Tensor Factorization Linked to External Data

Description

Model objects are updated in place to avoid memory issues. Nothing is returned.

Usage

train_Tucker(d, m, new.iter = 1, params)

Arguments

d	an input data object created with input_data
m	a Tucker_model object created with mk_model
new.iter	numeric number of iterations to run (def: 1)
params	List of parameters created with get_model_params()

Examples

data.params <- get_data_params(c('decomp=Tucker'))
toy <- mk_toy(data.params)
train.data <- input_data$new(mode1.X=toy$mode1.X[,-1],
                             mode2.X=toy$mode2.X[,-1],
                             mode3.X=toy$mode3.X[,-1],
                             resp=toy$resp)
model.params <- get_model_params(c('decomp=Tucker'))
toy.model <- mk_model(train.data, model.params)
toy.model$rand_init(model.params)

train(d=train.data, m=toy.model, new.iter=1, params=model.params)

BaTFLED3D documentation built on May 2, 2019, 2:38 p.m.