[mlpack-svn] r15652 - mlpack/trunk/src/mlpack/methods/linear_regression

fastlab-svn at coffeetalk-1.cc.gatech.edu fastlab-svn at coffeetalk-1.cc.gatech.edu
Sun Aug 25 12:29:04 EDT 2013


Author: rcurtin
Date: Sun Aug 25 12:29:03 2013
New Revision: 15652

Log:
Fix compatibility with older Armadillo versions and fix warning in
linear_regression_main.cpp.


Modified:
   mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp
   mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp

Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp	(original)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp	Sun Aug 25 12:29:03 2013
@@ -66,7 +66,7 @@
 
   // Get the predictions, but this ignores the intercept value (parameters[0]).
   predictions = arma::trans(arma::trans(
-      parameters(arma::span(1, parameters.n_elem - 1))) * points);
+      parameters.subvec(1, parameters.n_elem - 1)) * points);
 
   // Now add the intercept.
   predictions += parameters(0);

Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
==============================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp	(original)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp	Sun Aug 25 12:29:03 2013
@@ -58,7 +58,7 @@
 
   LinearRegression lr;
 
-  bool computeModel;
+  bool computeModel = false;
 
   // We want to determine if an input file XOR model file were given.
   if (trainName.empty()) // The user specified no input file.
@@ -72,7 +72,6 @@
   // The user specified an input file but no model file, no problems.
   else if (modelName.empty())
     computeModel = true;
-
   // The user specified both an input file and model file.
   // This is ambiguous -- which model should we use? A generated one or given
   // one?  Report error and exit.



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