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API Documentation

lazy_opls_da

Category: Statistical Models

Classes

lazy_opls_da

Parameters:

  • data (pd.DataFrame): DataFrame containing the dataset.
  • groups (list): List of class labels for each data sample.
  • working_dir (str): Directory path for storing output files.
  • feature_names (list, optional): Names of features, defaults to None.
  • n_components (int, optional): Number of components for OPLS-DA, defaults to 2.
  • scaling (str, optional): Scaling method ('pareto'), defaults to 'pareto'.
  • estimator (str, optional): Model estimator, defaults to 'opls'.
  • kfold (int, optional): Number of folds in cross-validation, defaults to 3.
  • random_state (int, optional): Random seed, defaults to 94.
  • auto_ncomp (bool, optional): Automatically choose the optimal number of components, defaults to True.
  • permutation (bool, optional): Conduct permutation tests, defaults to True.
  • VIP (bool, optional): Calculate VIP scores, defaults to True.
  • linear_regression (bool, optional): Conduct linear regression analysis, defaults to True.

Methods

init(data, groups, working_dir, feature_, n_components, scaling, estimator, kfold, random_state, auto_ncomp, permutation, n_permutation, n_jobs, VIP, VIP_threshold, linear_regression, FC_threshold, p_val_threshold)
fit(marker_color, custom_color, custom_shape, symbol_dict, custom_legend_name, marker_label, marker_size, marker_opacity, individual_ellipse)