fastml (version 0.2.0)

train_models: 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,
  task,
  algorithms,
  resampling_method,
  folds,
  repeats,
  tune_params,
  metric,
  summaryFunction = NULL,
  seed = 123,
  recipe,
  use_default_tuning = FALSE
)

Value

A list of trained model objects.

Arguments

train_data

Preprocessed training data frame.

label

Name of the target variable.

task

Type of task: "classification" or "regression".

algorithms

Vector of algorithm names to train.

resampling_method

Resampling method for cross-validation (e.g., "cv", "repeatedcv", "boot", "none").

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.

recipe

A recipe object for preprocessing.

use_default_tuning

Logical indicating whether to use default tuning grids when tune_params is NULL. Default is FALSE.