| #------------------------------------------------------------- |
| # |
| # 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 |
| # |
| # Unless required by applicable law or agreed to in writing, |
| # software distributed under the License is distributed on an |
| # "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. |
| # |
| #------------------------------------------------------------- |
| |
| # |
| # 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) |
| } |