[mlpack-git] master: Minor syntax and formatting changes. (7a8b0e1)

[gitdub at big.cc.gt.atl.ga.us]

Repository : https://github.com/mlpack/mlpack

On branch  : master
Link       : https://github.com/mlpack/mlpack/compare/dc2c5c68dc4bfcdd2075b1a0fd2d641fce651669...7a8b0e1292677b71888fad313772c63bcf0e7b80

>---------------------------------------------------------------

commit 7a8b0e1292677b71888fad313772c63bcf0e7b80
Author: Ryan Curtin <ryan at ratml.org>
Date:   Wed Sep 30 09:35:05 2015 -0400

    Minor syntax and formatting changes.


>---------------------------------------------------------------

7a8b0e1292677b71888fad313772c63bcf0e7b80
 .../softmax_regression_function.cpp                | 29 +++++++++++-----------
 .../softmax_regression_function.hpp                | 27 +++++++++++---------
 2 files changed, 30 insertions(+), 26 deletions(-)

diff --git a/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp b/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
index a3417af..3257015 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression_function.cpp
@@ -9,11 +9,12 @@
 using namespace mlpack;
 using namespace mlpack::regression;
 
-SoftmaxRegressionFunction::SoftmaxRegressionFunction(const arma::mat& data,
-                                                     const arma::Row<size_t>& labels,
-                                                     const size_t numClasses,
-                                                     const double lambda,
-                                                     const bool fitIntercept) :
+SoftmaxRegressionFunction::SoftmaxRegressionFunction(
+    const arma::mat& data,
+    const arma::Row<size_t>& labels,
+    const size_t numClasses,
+    const double lambda,
+    const bool fitIntercept) :
     data(data),
     numClasses(numClasses),
     lambda(lambda),
@@ -36,21 +37,21 @@ const arma::mat SoftmaxRegressionFunction::InitializeWeights()
   return InitializeWeights(data.n_rows, numClasses, fitIntercept);
 }
 
-const arma::mat SoftmaxRegressionFunction::
-InitializeWeights(const size_t featureSize,
-                  const size_t numClasses,
-                  const bool fitIntercept)
+const arma::mat SoftmaxRegressionFunction::InitializeWeights(
+    const size_t featureSize,
+    const size_t numClasses,
+    const bool fitIntercept)
 {
     arma::mat parameters;
     InitializeWeights(parameters, featureSize, numClasses, fitIntercept);
     return parameters;
 }
 
-void SoftmaxRegressionFunction::
-InitializeWeights(arma::mat &weights,
-                  const size_t featureSize,
-                  const size_t numClasses,
-                  const bool fitIntercept)
+void SoftmaxRegressionFunction::InitializeWeights(
+    arma::mat &weights,
+    const size_t featureSize,
+    const size_t numClasses,
+    const bool fitIntercept)
 {
   // Initialize values to 0.005 * r. 'r' is a matrix of random values taken from
   // a Gaussian distribution with mean zero and variance one.
diff --git a/src/mlpack/methods/softmax_regression/softmax_regression_function.hpp b/src/mlpack/methods/softmax_regression/softmax_regression_function.hpp
index e56355f..7a69044 100644
--- a/src/mlpack/methods/softmax_regression/softmax_regression_function.hpp
+++ b/src/mlpack/methods/softmax_regression/softmax_regression_function.hpp
@@ -37,25 +37,26 @@ class SoftmaxRegressionFunction
   const arma::mat InitializeWeights();
 
   /**
-   * Initialize Softmax Regression weights(trainable parameters) with
-   * the given parameters.
-   * @param featureSize The features size of the training set
+   * Initialize Softmax Regression weights (trainable parameters) with the given
+   * parameters.
+   *
+   * @param featureSize The number of features in the training set.
    * @param numClasses Number of classes for classification.
-   * @param fitIntercept Intercept term flag.
-   * @return weights after initialize
+   * @param fitIntercept If true, an intercept is fitted.
+   * @return Initialized model weights.
    */
   static const arma::mat InitializeWeights(const size_t featureSize,
                                            const size_t numClasses,
                                            const bool fitIntercept = false);
 
   /**
-   * Initialize Softmax Regression weights(trainable parameters) with
-   * the given parameters.
-   * @paaram weights weights want to initialize
-   * @param featureSize The features size of the training set
+   * Initialize Softmax Regression weights (trainable parameters) with the given
+   * parameters.
+   *
+   * @param weights This will be filled with the initialized model weights.
+   * @param featureSize The number of features in the training set.
    * @param numClasses Number of classes for classification.
    * @param fitIntercept Intercept term flag.
-   * @return weights after initialize
    */
   static void InitializeWeights(arma::mat &weights,
                                 const size_t featureSize,
@@ -113,8 +114,10 @@ class SoftmaxRegressionFunction
 
   //! Gets the features size of the training data
   size_t FeatureSize() const
-  { return fitIntercept ? initialPoint.n_cols - 1 :
-                          initialPoint.n_cols; }
+  {
+    return fitIntercept ? initialPoint.n_cols - 1 :
+                          initialPoint.n_cols;
+  }
 
   //! Sets the regularization parameter.
   double& Lambda() { return lambda; }