#-------------------------------------------------------------
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#
#   http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing,
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied.  See the License for the
# specific language governing permissions and limitations
# under the License.
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#-------------------------------------------------------------

#
# INPUT PARAMETERS:
# ----------------------------------------------------------------------------
# NAME                              TYPE      DEFAULT  MEANING
# ----------------------------------------------------------------------------
# X                                 Matrix    ---      Matrix of feature vectors.
# y                                 Matrix    ---      1-column matrix of response values.
# icpt                              Integer   0        Intercept presence, shifting and rescaling the columns of X
# reg                               Double    1e-7     Regularization constant (lambda) for L2-regularization. set to nonzero for highly dependant/sparse/numerous features
# tol                               Double    1e-7     Tolerance (epsilon); conjugate gradient procedure terminates early if L2 norm of the beta-residual is less than tolerance * its initial norm
# maxi                              Integer   0        Maximum number of conjugate gradient iterations. 0 = no maximum
# verbose                           Boolean   TRUE     If TRUE print messages are activated
#
#
# RETURN VALUES
# ----------------------------------------------------------------------------
# NAME     TYPE      DEFAULT  MEANING
# ----------------------------------------------------------------------------
# B        String    "B.mtx"  The model fit
# ----------------------------------------------------------------------------

m_lm = function(Matrix[Double] X, Matrix[Double] y, Integer icpt = 0, Double reg = 1e-7, Double tol = 1e-7, Integer maxi = 0, Boolean verbose = TRUE)
    return (Matrix[Double] B) {
  if( ncol(X) <= 1024 )
    B = lmDS(X, y, icpt, reg, verbose)
  else
    B = lmCG(X, y, icpt, reg, tol, maxi, verbose)
}
