test_Tucker: Perform 'cold start' prediction for Tucker models
In BaTFLED3D: Bayesian Tensor Factorization Linked to External Data

Description Usage Arguments Value Examples

Perform 'cold start' prediction for Tucker models

1	test_Tucker(d, m)

`d`	an input data object created with `input_data`
`m`	a `Tucker_model` object created with `mk_model`

Response tensor generated by multiplying the input data through the trained model

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)

resp <- test_Tucker(train.data, toy.model)