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Retrieve and Preprocess Data for Machine Learning Models

Source: R/get_Data_formatted_for_ml_and_best.m.R
get_Data_formatted_for_ml_and_best.m.Rd

This function processes data from a given SQLite database or XPT file, calculates liver toxicity scores, and prepares data for machine learning models. It can also tune hyperparameters and apply error correction methods.

Usage

get_Data_formatted_for_ml_and_best.m(
  path_db,
  rat_studies = FALSE,
  studyid_metadata = NULL,
  fake_study = FALSE,
  use_xpt_file = FALSE,
  Round = FALSE,
  Impute = FALSE,
  reps,
  holdback,
  Undersample = FALSE,
  hyperparameter_tuning = FALSE,
  error_correction_method
)

Arguments

path_db

A character string representing the path to the SQLite database or XPT file.

rat_studies

A logical flag to filter for rat studies (default is FALSE).

studyid_metadata

A data frame containing metadata for the study IDs. If NULL, metadata is generated (default is NULL).

fake_study

A logical flag to use fake study data (default is FALSE).

use_xpt_file

A logical flag to indicate whether to use an XPT file instead of a SQLite database (default is FALSE).

Round

A logical flag to round liver toxicity scores (default is FALSE).

Impute

A logical flag to impute missing values in the dataset (default is FALSE).

reps

An integer specifying the number of repetitions for cross-validation.

holdback

A numeric value indicating the fraction of data to hold back for validation.

Undersample

A logical flag to undersample the majority class (default is FALSE).

hyperparameter_tuning

A logical flag to perform hyperparameter tuning (default is FALSE).

error_correction_method

A character string specifying the error correction method. Must be one of 'Flip', 'Prune', or 'None'.

Value

A list containing:

Data

A data frame containing the preprocessed data ready for machine learning.

best.m

The best machine learning model after hyperparameter tuning, if applicable.

Details

This function performs several key steps:

  • Retrieves study IDs from an SQLite database or XPT file.

  • Generates or uses provided study metadata, including a random assignment of "Target_Organ" values (either "Liver" or "not_Liver").

  • Calculates liver toxicity scores using the get_liver_om_lb_mi_tox_score_list function.

  • Harmonizes the calculated scores using the get_col_harmonized_scores_df function.

  • Prepares the data for machine learning and tunes hyperparameters (if enabled) using the get_ml_data_and_tuned_hyperparameters function.

  • Returns the processed data and the best model.

Examples

if (FALSE) { # \dontrun{
result <- get_Data_formatted_for_ml_and_best.m(
  path_db = "path/to/database.db",
  rat_studies = TRUE,
  reps = 5,
  holdback = 0.2,
  error_correction_method = "Flip"
)

# Access the processed data and the best model
processed_data <- result$Data
best_model <- result$best.m
} # }