RobustPrediction (version 0.1.7)

tuneandtrainInt: Tune and Train by tuning method Int

Description

This function tunes and trains a specified classifier using internal cross-validation. The classifier is specified by the `classifier` argument, and the function delegates to the appropriate tuning and training function based on this choice.

Usage

tuneandtrainInt(data, classifier, ...)

Value

A list containing the results from the specific classifier's tuning and training process. The list typically includes:

• best_hyperparams: The best hyperparameters selected by cross-validation.

• best_model: The final trained model using the selected hyperparameters.

• final_auc: Cross-validation results (AUC).

Arguments

data

A data frame containing the training data. The first column should be the response variable (factor), and the remaining columns should be the predictor variables.

classifier

A character string specifying the classifier to use. Must be one of 'boosting', 'rf', 'lasso', 'ridge', 'svm'.

...

Additional arguments to pass to the specific classifier function.

Examples

# Load sample data
data(sample_data_train)

# Example usage with Lasso
result_lasso <- tuneandtrainInt(sample_data_train, classifier = "lasso",
  maxit = 120000, nlambda = 100)
result_lasso$best_lambda
result_lasso$best_model
result_lasso$final_auc
result_lasso$active_set_Train

# Example usage with Ridge
result_ridge <- tuneandtrainInt(sample_data_train, classifier = "ridge", 
  maxit = 120000, nlambda = 100)
result_ridge$best_lambda
result_ridge$best_model
result_ridge$final_auc