combine_hp_performance: Combine hyperparameter performance metrics for multiple...

In SchlossLab/mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

Combine hyperparameter performance metrics for multiple train/test splits

Description

Combine hyperparameter performance metrics for multiple train/test splits generated by, for instance, looping in R or using a snakemake workflow on a high-performance computer.

Usage

combine_hp_performance(trained_model_lst)

Arguments

trained_model_lst

List of trained models.

Value

Named list:

• dat: Dataframe of performance metric for each group of hyperparameters

• params: Hyperparameters tuned.

• Metric: Performance metric used.

Author(s)

Zena Lapp, [e-mail]

Examples

## Not run: 
results <- lapply(seq(100, 102), function(seed) {
  run_ml(otu_small, "glmnet", seed = seed, cv_times = 2, kfold = 2)
})
models <- lapply(results, function(x) x$trained_model)
combine_hp_performance(models)

## End(Not run)

SchlossLab/mikropml documentation built on Aug. 24, 2023, 9:51 p.m.