comparison pycaret_train.py @ 9:c6c1f8777aae draft

planemo upload for repository https://github.com/goeckslab/gleam commit 4a11e8a4c4e9daa884bddedfa47090476c517667

8:1aed7d47c5ec

        action="store_true",
        default=False,
        help="Tune the best model hyperparameters after training",
    )
    parser.add_argument(
        "--random_seed",
        type=int,
        default=42,
        help="Random seed for PyCaret setup",
    )
    parser.add_argument(
        "--test_file",
        type=str,
        default=None,
        help="Path to the test data file",
    )

    args = parser.parse_args()

    # Normalize cross-validation flags: --no_cross_validation overrides --cross_validation
    if args.no_cross_validation:
        args.cross_validation = False
    # If --cross_validation was passed, args.cross_validation is True
    # If neither was passed, args.cross_validation remains None

    # Build the model_kwargs dict from CLI args
    model_kwargs = {
        "train_size": args.train_size,

        "polynomial_features": args.polynomial_features,
        "feature_interaction": args.feature_interaction,
        "feature_ratio": args.feature_ratio,
        "fix_imbalance": args.fix_imbalance,
        "tune_model": args.tune_model,
    }
    LOG.info(f"Model kwargs: {model_kwargs}")

    # If the XML passed a comma-separated string in a single list element, split it out
    if args.models:

9:c6c1f8777aae

        action="store_true",
        default=False,
        help="Tune the best model hyperparameters after training",
    )
    parser.add_argument(
        "--test_file",
        type=str,
        default=None,
        help="Path to the test data file",
    )
    parser.add_argument(
        "--random_seed",
        type=int,
        default=42,
        help="Random seed for PyCaret setup",
    )
    parser.add_argument(
        "--probability_threshold",
        type=float,
        default=None,
        help="Probability threshold for classification decision,",
    )

    args = parser.parse_args()

    # Normalize cross-validation flags: --no_cross_validation overrides --cross_validation
    if args.no_cross_validation:
        args.cross_validation = False
    # If --cross_validation was passed,  args.cross_validation is True
    # If neither was passed, args.cross_validation remains None

    # Build the model_kwargs dict from CLI args
    model_kwargs = {
        "train_size": args.train_size,

        "polynomial_features": args.polynomial_features,
        "feature_interaction": args.feature_interaction,
        "feature_ratio": args.feature_ratio,
        "fix_imbalance": args.fix_imbalance,
        "tune_model": args.tune_model,
        "probability_threshold": args.probability_threshold,
    }
    LOG.info(f"Model kwargs: {model_kwargs}")

    # If the XML passed a comma-separated string in a single list element, split it out
    if args.models: