[mlpack-svn] r10864 - mlpack/trunk/src/mlpack/methods/linear_regression

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

Author: vlad321
Date: 2011-12-16 15:29:44 -0500 (Fri, 16 Dec 2011)
New Revision: 10864

Modified:
   mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp
   mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
Log:
Formatting of /linear_regression


Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp	2011-12-16 20:14:10 UTC (rev 10863)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression.cpp	2011-12-16 20:29:44 UTC (rev 10864)
@@ -21,15 +21,15 @@
   // We store the number of rows of the predictors.
   // Reminder: Armadillo stores the data transposed from how we think of it,
   //           that is, columns are actually rows (see: column major order).
-  size_t n_cols = predictors.n_cols;
+  size_t nCols = predictors.n_cols;
 
   // Here we add the row of ones to the predictors.
   arma::rowvec ones;
-  ones.ones(n_cols);
+  ones.ones(nCols);
   predictors.insert_rows(0, ones);
 
   // We set the parameters to the correct size and initialize them to zero.
-  parameters.zeros(n_cols);
+  parameters.zeros(nCols);
 
   // We compute the QR decomposition of the predictors.
   // We transpose the predictors because they are in column major order.
@@ -56,21 +56,21 @@
 void LinearRegression::Predict(const arma::mat& points, arma::vec& predictions)
 {
   // We get the number of columns and rows of the dataset.
-  const size_t n_cols = points.n_cols;
-  const size_t n_rows = points.n_rows;
+  const size_t nCols = points.n_cols;
+  const size_t nRows = points.n_rows;
 
   // We want to be sure we have the correct number of dimensions in the dataset.
-  Log::Assert(n_rows == parameters.n_rows - 1);
+  Log::Assert(nRows == parameters.n_rows - 1);
 
-  predictions.zeros(n_cols);
+  predictions.zeros(nCols);
   // We set all the predictions to the intercept value initially.
   predictions += parameters(0);
 
   // Now we iterate through the dimensions of the data and parameters.
-  for (size_t i = 1; i < n_rows + 1; ++i)
+  for (size_t i = 1; i < nRows + 1; ++i)
   {
     // Now we iterate through each row, or point, of the data.
-    for (size_t j = 0; j < n_cols; ++j)
+    for (size_t j = 0; j < nCols; ++j)
     {
       // Increment each prediction value by x_i * a_i, or the next dimensional
       // coefficient and x value.

Modified: mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp
===================================================================
--- mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp	2011-12-16 20:14:10 UTC (rev 10863)
+++ mlpack/trunk/src/mlpack/methods/linear_regression/linear_regression_main.cpp	2011-12-16 20:29:44 UTC (rev 10864)
@@ -43,18 +43,18 @@
   // Handle parameters
   CLI::ParseCommandLine(argc, argv);
 
-  const string train_name = CLI::GetParam<string>("input_file");
-  const string test_name = CLI::GetParam<string>("test_file");
-  const string response_name = CLI::GetParam<string>("input_responses");
-  const string output_file = CLI::GetParam<string>("output_file");
-  const string output_predictions = CLI::GetParam<string>("output_predictions");
+  const string trainName = CLI::GetParam<string>("input_file");
+  const string testName = CLI::GetParam<string>("test_file");
+  const string responseName = CLI::GetParam<string>("input_responses");
+  const string outputFile = CLI::GetParam<string>("outputFile");
+  const string outputPredictions = CLI::GetParam<string>("outputPredictions");
 
   mat regressors;
   mat responses;
-  data::Load(train_name.c_str(), regressors, true);
+  data::Load(trainName.c_str(), regressors, true);
 
   // Are the responses in a separate file?
-  if (response_name == "")
+  if (responseName == "")
   {
     // The initial predictors for y, Nx1
     responses = trans(regressors.row(regressors.n_rows - 1));
@@ -63,7 +63,7 @@
   else
   {
     // The initial predictors for y, Nx1
-    data::Load(response_name.c_str(), responses, true);
+    data::Load(responseName.c_str(), responses, true);
 
     if (responses.n_rows == 1)
       responses = trans(responses); // Probably loaded backwards, but that's ok.
@@ -79,13 +79,13 @@
   LinearRegression lr(regressors, responses.unsafe_col(0));
 
   // Save the parameters.
-  data::Save(output_file.c_str(), lr.Parameters(), false);
+  data::Save(outputFile.c_str(), lr.Parameters(), false);
 
   // Did we want to predict, too?
-  if (test_name != "")
+  if (testName != "")
   {
     arma::mat points;
-    data::Load(test_name.c_str(), points, true);
+    data::Load(testName.c_str(), points, true);
 
     if (points.n_rows != regressors.n_rows)
       Log::Fatal << "The test data must have the same number of columns as the "
@@ -95,6 +95,6 @@
     lr.Predict(points, predictions);
 
     // Save predictions.
-    data::Save(output_predictions.c_str(), predictions, false);
+    data::Save(outputPredictions.c_str(), predictions, false);
   }
 }