mdr/utils/utils.py
def _mdr_predict(X, Y, labels):
    """Fits a MDR model to variables X and Y with the given labels, then returns the resulting predictions

    This is a convenience method that should only be used internally.

    Parameters
    ----------
    X: array-like (# samples)
        An array of values corresponding to one feature in the MDR model
    Y: array-like (# samples)
        An array of values corresponding to one feature in the MDR model
    labels: array-like (# samples)
        The class labels corresponding to features X and Y

    Returns
    ----------
    predictions: array-like (# samples)
        The predictions from the fitted MDR model

    """
    return MDR().fit_predict(np.column_stack((X, Y)), labels)
def _mdr_predict(X, Y, labels):
    return MDR().fit_predict(np.column_stack((X, Y)), labels)
def _mdr_predict ( X , Y , labels ) : return MDR ( ) . fit_predict ( np . column_stack ( ( X , Y ) ) , labels )
Fits a MDR model to variables X and Y with the given labels, then returns the resulting predictions

    This is a convenience method that should only be used internally.

    Parameters
    ----------
    X: array-like (# samples)
        An array of values corresponding to one feature in the MDR model
    Y: array-like (# samples)
        An array of values corresponding to one feature in the MDR model
    labels: array-like (# samples)
        The class labels corresponding to features X and Y

    Returns
    ----------
    predictions: array-like (# samples)
        The predictions from the fitted MDR model
Fits a MDR model to variables X and Y with the given labels then returns the resulting predictions