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# Autogenerated By   : src/main/python/generator/generator.py
# Autogenerated From : scripts/builtin/lmCG.dml

from typing import Dict, Iterable

from systemds.operator import OperationNode, Matrix, Frame, List, MultiReturn, Scalar
from systemds.script_building.dag import OutputType
from systemds.utils.consts import VALID_INPUT_TYPES


def lmCG(X: Matrix,
         y: Matrix,
         **kwargs: Dict[str, VALID_INPUT_TYPES]):
    """
     The lmCG function solves linear regression using the conjugate gradient algorithm
    
    
    
    :param X: Matrix of feature vectors.
    :param y: 1-column matrix of response values.
    :param icpt: Intercept presence, shifting and rescaling the columns of X
    :param reg: Regularization constant (lambda) for L2-regularization. set to nonzero
        for highly dependant/sparse/numerous features
    :param tol: Tolerance (epsilon); conjugate gradient procedure terminates early if L2
        norm of the beta-residual is less than tolerance * its initial norm
    :param maxi: Maximum number of conjugate gradient iterations. 0 = no maximum
    :param verbose: If TRUE print messages are activated
    :return: The model fit
    """

    params_dict = {'X': X, 'y': y}
    params_dict.update(kwargs)
    return Matrix(X.sds_context,
        'lmCG',
        named_input_nodes=params_dict)
