[mlpack-svn] r15851 - mlpack/trunk/src/mlpack/methods/lars

[fastlab-svn at coffeetalk-1.cc.gatech.edu]

Author: rcurtin
Date: Thu Sep 26 15:59:29 2013
New Revision: 15851

Log:
Update documentation.


Modified:
   mlpack/trunk/src/mlpack/methods/lars/lars_main.cpp

Modified: mlpack/trunk/src/mlpack/methods/lars/lars_main.cpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/lars/lars_main.cpp	(original)
+++ mlpack/trunk/src/mlpack/methods/lars/lars_main.cpp	Thu Sep 26 15:59:29 2013
@@ -21,12 +21,13 @@
     "      0.5 lambda_2 ||beta||_2^2\n\n"
     "If lambda_1 > 0 and lambda_2 = 0, the problem is the LASSO.\n"
     "If lambda_1 > 0 and lambda_2 > 0, the problem is the Elastic Net.\n"
-    "If lambda_1 = 0 and lambda_2 > 0, the problem is Ridge Regression.\n"
+    "If lambda_1 = 0 and lambda_2 > 0, the problem is ridge regression.\n"
     "If lambda_1 = 0 and lambda_2 = 0, the problem is unregularized linear "
     "regression.\n"
     "\n"
     "For efficiency reasons, it is not recommended to use this algorithm with "
-    "lambda_1 = 0.\n");
+    "lambda_1 = 0.  In that case, use the 'linear_regression' program, which "
+    "implements both unregularized linear regression and ridge regression.\n");
 
 PARAM_STRING_REQ("input_file", "File containing covariates (X).",
     "i");