[mlpack-svn] r10529 - mlpack/trunk/src/mlpack/methods/lars

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

Author: niche
Date: 2011-12-03 11:51:36 -0500 (Sat, 03 Dec 2011)
New Revision: 10529

Removed:
   mlpack/trunk/src/mlpack/methods/lars/old_main.cc
Log:


Deleted: mlpack/trunk/src/mlpack/methods/lars/old_main.cc
===================================================================
--- mlpack/trunk/src/mlpack/methods/lars/old_main.cc	2011-12-03 16:45:10 UTC (rev 10528)
+++ mlpack/trunk/src/mlpack/methods/lars/old_main.cc	2011-12-03 16:51:36 UTC (rev 10529)
@@ -1,88 +0,0 @@
-/** @file main.cc
- *
- *  Driver file for testing LARS
- *
- *  @author Nishant Mehta (niche)
- */
-
-#include <fastlib/fastlib.h>
-#include <armadillo>
-
-#include "lars.h"
-
-using namespace arma;
-using namespace std;
-
-int main(int argc, char* argv[]) {
-  
-  //bool use_cholesky = false;
-  double lambda_1 = 0.1;
-  double lambda_2 = 0.5;
-  
-  u32 n = 100;
-  u32 p = 10;
-
-  mat X = randu<mat>(n,p);
-  
-  
-  mat X_reg = zeros(n + p, p);
-  X_reg(span(0, n - 1), span::all) = X;
-  for(u32 i = 0; i < p; i++) {
-    X_reg(n + i, i) = sqrt(lambda_2);
-  }
-  //X_reg.print("X_reg");
-  
-  
-  
-  mat beta_true = zeros(p,1);
-  beta_true(0) = 1;
-  beta_true(1) = -1;
-  beta_true(9) = 1;
-  
-  
-  vec y = X * beta_true + 0.1 * randu<vec>(n);
-  //vec y = randu(n);
-  //y.load("y.dat", raw_ascii);
-  //y.load("x.dat", raw_ascii);
-  
-  
-  vec y_reg = zeros(n + p);
-  y_reg.subvec(0, n - 1) = y;
-  //y_reg.print("y_reg");
-  
-  
-  mat Gram = trans(X) * X;
-  
-  Lars lars;
-  //lars.Init(X, y, false, lambda_1);
-  //lars.SetGram(Gram.memptr(), X.n_cols);
-  //lars.Init(X, y, false, lambda_1, lambda_2);
-  lars.Init(X_reg, y_reg, false, lambda_1);
-  //lars.Init(X_reg, y_reg, use_cholesky);
-  
-  lars.DoLARS();
-  
-  u32 path_length = lars.beta_path().size();
-  
-  mat beta_matrix = mat(p, path_length);
-  for(u32 i = 0; i < path_length; i++) {
-    beta_matrix.col(i) = lars.beta_path()[i];
-  }
-  //beta_matrix.print("beta matrix");
-
-  vec lambda_path_vec = conv_to< colvec >::from(lars.lambda_path());
-  //lambda_path_vec.print("lambda path");
-  
-  
-  //X.save("X.dat", raw_ascii);
-  //y.save("y.dat", raw_ascii);
-
-  ////beta_matrix.save("beta.dat", raw_ascii);
-  ////lambda_path_vec.save("lambda.dat", raw_ascii);
-  
-  
-  vec beta;
-  lars.Solution(beta);
-  
-  beta.print("final beta");
-}