train_models {fastml}R Documentation

Train Specified Machine Learning Algorithms on the Training Data

Description

Trains specified machine learning algorithms on the preprocessed training data.

Usage

train_models(
  train_data,
  label,
  algorithms,
  resampling_method,
  folds,
  repeats = NULL,
  tune_params,
  metric,
  summaryFunction = NULL,
  seed = 123
)

Arguments

train_data

Preprocessed training data frame.

label

Name of the target variable.

algorithms

Vector of algorithm names to train.

resampling_method

Resampling method for cross-validation (e.g., "cv", "repeatedcv").

folds

Number of folds for cross-validation.

repeats

Number of times to repeat cross-validation (only applicable for methods like "repeatedcv").

tune_params

List of hyperparameter tuning ranges.

metric

The performance metric to optimize.

summaryFunction

A custom summary function for model evaluation. Default is NULL.

seed

An integer value specifying the random seed for reproducibility.

Value

A list of trained model objects.


[Package fastml version 0.1.0 Index]