Skip to contents

Base learner: tune hyperparameters and retrieve the best model

Source: R/base_learner.R
fit_base_learner.Rd

Multilayer perceptron model with different configurations of hidden units, dropout, activation, and learning rate using brulee and tidymodels. With proper settings, users can utilize graphics processing units (GPU) to speed up the training process.

Usage

fit_base_learner(
  learner = c("mlp", "xgb", "lgb", "elnet"),
  dt_full,
  r_subsample = 0.3,
  model = NULL,
  folds = 5L,
  cv_mode = c("spatiotemporal", "spatial", "temporal"),
  args_generate_cv = NULL,
  tune_mode = "grid",
  tune_bayes_iter = 10L,
  tune_grid_in = NULL,
  tune_grid_size = 10L,
  learn_rate = 0.1,
  yvar = "Arithmetic.Mean",
  xvar = seq(5, ncol(dt_sample)),
  nthreads = 8L,
  trim_resamples = FALSE,
  return_best = TRUE,
  ...
)

Arguments

learner

character(1). The base learner to be used. Default is "mlp". Available options are "mlp", "xgb", "lgb", "elnet".

dt_full

The full data table to be used for prediction.

r_subsample

numeric(1). The proportion of rows to be used.

model

The parsnip model object. Preferably generated from switch_model.

folds

integer(1). Number of cross-validation folds. If NULL, cv_mode should be defined to be used in rsample::vfold_cv.

cv_mode

character(1). Cross-validation mode. Default is "spatiotemporal". Available options are "spatiotemporal", "spatial", "temporal".

args_generate_cv

List of arguments to be passed to switch_generate_cv_rset function.

tune_mode

character(1). Hyperparameter tuning mode. Default is "grid", "bayes" is acceptable.

tune_bayes_iter

integer(1). The number of iterations for Bayesian optimization. Default is 10. Only used when tune_mode = "bayes".

tune_grid_in

data.frame object that includes the grid for hyperparameter tuning. tune_grid_size rows will be randomly picked from this data.frame for grid search.

tune_grid_size

integer(1). The number of grid size for hyperparameter tuning. Default is 10. Only used when tune_mode = "grid".

learn_rate

The learning rate for the model. For branching purpose. Default is 0.1.

yvar

The target variable.

xvar

The predictor variables.

nthreads

integer(1). The number of threads to be used for tuning. Default is 8L. learner = "elnet" will utilize the multiple threads in future::multicore() plan.

trim_resamples

logical(1). Default is TRUE, which replaces the actual data.frames in splits column of tune_results object with NA.

return_best

logical(1). If TRUE, the best tuned model is returned.

...

Additional arguments to be passed.

Value

The fitted workflow.

Details

LightGBM model is fitted at the defined rate (r_subsample) of the input dataset by grid or Bayesian optimization search. With proper settings, users can utilize graphics processing units (GPU) to speed up the training process.

XGBoost model is fitted at the defined rate (r_subsample) of the input dataset by grid or Bayesian optimization search. With proper settings, users can utilize graphics processing units (GPU) to speed up the training process.

Elastic net model is fitted at the defined rate (r_subsample) of the input dataset by grid search or Bayesian optimization.

  • MLP: Hyperparameters hidden_units, dropout, activation, and learn_rate are tuned. With tune_mode = "grid", users can modify learn_rate explicitly, and other hyperparameters will be predefined (56 combinations per learn_rate for mlp).

  • XGBoost: Hyperparameters mtry, ntrees, and learn_rate are tuned. With tune_mode = "grid", users can modify learn_rate explicitly, and other hyperparameters will be predefined (30 combinations per learn_rate).

  • LightGBM: Hyperparameters mtry, ntrees, and learn_rate are tuned. With tune_mode = "grid", users can modify learn_rate explicitly, and other hyperparameters will be predefined (30 combinations per learn_rate).

  • Elastic net: Hyperparameters mixture and penalty are tuned.

Tuning is performed based on random grid search (size = 10).

Note

tune package should be 1.2.0 or higher. brulee, xgboost, and lightgbm should be installed with GPU support. Grid search is not activated in this function, regardless of other parts' description.