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Choose Top Base Models for Stacking Based on Accuracy or AUC Scores

Source: R/machine_learning.R
choose_base_models.Rd

This function selects three base models for stacking based on either Accuracy or AUC metrics. It chooses the top models from different categories (e.g., tree-based methods, linear models, instance-based methods) according to the specified metric.

Usage

choose_base_models(models, metric = "Accuracy")

Arguments

models

A list of trained machine learning models. Each model must contain a resample data frame with performance metrics (Accuracy, AUROC, AUPRC) from cross-validation.

metric

A character string specifying the metric to use for model selection. Can be either "Accuracy", "AUROC", or "AUPRC". Default is "Accuracy".

Value

A character vector containing the names of the top models selected based on the specified metric.

Examples

if (FALSE) { # \dontrun{
base_models = choose_base_models(models = ml_models, metric = "AUROC")
} # }