Transfer Learning Workflow

Use unsupervised pre-training (e.g., autoencoder features) before supervised learning

Usage

tl_transfer_learning(
  data,
  formula,
  pretrain_method = "pca",
  supervised_method = "tree",
  ...
)

Arguments

data

Training data

formula

Model formula

pretrain_method

Pre-training method: "pca", "autoencoder"

supervised_method

Supervised learning method (default: "tree", which handles both regression and classification with any number of classes). "logistic" is binary-only and errors on a response with more than two levels.

...

Additional arguments

Value

A list with class "tidylearn_transfer" containing:

pretrain_model

The fitted dimensionality reduction model.

supervised_model

The fitted supervised tidylearn model.

formula

The model formula.

method

The supervised learning method used.

Examples

# \donttest{
model <- tl_transfer_learning(iris, Species ~ .,
  pretrain_method = "pca", supervised_method = "tree")
#> Transfer Learning Workflow
#> ==========================
#> [Phase 1] Unsupervised pre-training with pca...
#> [Phase 2] Supervised learning with tree...
# }