[mlpack-git] master, mlpack-1.0.x: First pass -- move files to match naming policy, change initialize() to Initialize(), standardize comment formatting, fix some Doxygen commands. No serious functionality changes. (519e791)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Thu Mar 5 21:51:31 EST 2015
Repository : https://github.com/mlpack/mlpack
On branches: master,mlpack-1.0.x
Link : https://github.com/mlpack/mlpack/compare/904762495c039e345beba14c1142fd719b3bd50e...f94823c800ad6f7266995c700b1b630d5ffdcf40
>---------------------------------------------------------------
commit 519e791ef5de4d5e66bea9a40d008e6e06746e46
Author: Ryan Curtin <ryan at ratml.org>
Date: Mon Jul 7 14:07:54 2014 +0000
First pass -- move files to match naming policy, change initialize() to
Initialize(), standardize comment formatting, fix some Doxygen commands. No
serious functionality changes.
>---------------------------------------------------------------
519e791ef5de4d5e66bea9a40d008e6e06746e46
src/mlpack/methods/perceptron/CMakeLists.txt | 6 +-
.../InitializationMethods/random_init.hpp | 31 ------
.../perceptron/InitializationMethods/zero_init.hpp | 34 ------
.../CMakeLists.txt | 0
.../initialization_methods/random_init.hpp | 35 ++++++
.../initialization_methods/zero_init.hpp | 37 +++++++
.../CMakeLists.txt | 2 +-
.../simple_weight_update.hpp} | 0
src/mlpack/methods/perceptron/perceptron.hpp | 104 ++++++++----------
src/mlpack/methods/perceptron/perceptron_impl.cpp | 118 --------------------
src/mlpack/methods/perceptron/perceptron_impl.hpp | 122 +++++++++++++++++++++
11 files changed, 243 insertions(+), 246 deletions(-)
diff --git a/src/mlpack/methods/perceptron/CMakeLists.txt b/src/mlpack/methods/perceptron/CMakeLists.txt
index c25c549..fa5e980 100644
--- a/src/mlpack/methods/perceptron/CMakeLists.txt
+++ b/src/mlpack/methods/perceptron/CMakeLists.txt
@@ -4,7 +4,7 @@ cmake_minimum_required(VERSION 2.8)
# Anything not in this list will not be compiled into MLPACK.
set(SOURCES
perceptron.hpp
- perceptron_impl.cpp
+ perceptron_impl.hpp
)
# Add directory name to sources.
@@ -16,8 +16,8 @@ endforeach()
# the parent scope).
set(MLPACK_SRCS ${MLPACK_SRCS} ${DIR_SRCS} PARENT_SCOPE)
-add_subdirectory(InitializationMethods)
-add_subdirectory(LearnPolicy)
+add_subdirectory(initialization_methods)
+add_subdirectory(learning_policies)
add_executable(percep
perceptron_main.cpp
diff --git a/src/mlpack/methods/perceptron/InitializationMethods/random_init.hpp b/src/mlpack/methods/perceptron/InitializationMethods/random_init.hpp
deleted file mode 100644
index 7cdeb19..0000000
--- a/src/mlpack/methods/perceptron/InitializationMethods/random_init.hpp
+++ /dev/null
@@ -1,31 +0,0 @@
-/*
- * @file: randominit.hpp
- * @author: Udit Saxena
- *
- */
-
-#ifndef _MLPACK_METHOS_PERCEPTRON_RANDOMINIT
-#define _MLPACK_METHOS_PERCEPTRON_RANDOMINIT
-
-#include <mlpack/core.hpp>
-/*
-This class is used to initialize weights for the
-weightVectors matrix in a random manner.
-*/
-namespace mlpack {
-namespace perceptron {
- class RandomInitialization
- {
- public:
- RandomInitialization()
- { }
-
- inline static void initialize(arma::mat& W, size_t row, size_t col)
- {
- W = arma::randu<arma::mat>(row,col);
- }
- }; // class RandomInitialization
-}; // namespace perceptron
-}; // namespace mlpack
-
-#endif
\ No newline at end of file
diff --git a/src/mlpack/methods/perceptron/InitializationMethods/zero_init.hpp b/src/mlpack/methods/perceptron/InitializationMethods/zero_init.hpp
deleted file mode 100644
index 7115c81..0000000
--- a/src/mlpack/methods/perceptron/InitializationMethods/zero_init.hpp
+++ /dev/null
@@ -1,34 +0,0 @@
-/*
- * @file: zeroinit.hpp
- * @author: Udit Saxena
- *
- */
-
-#ifndef _MLPACK_METHOS_PERCEPTRON_ZEROINIT
-#define _MLPACK_METHOS_PERCEPTRON_ZEROINIT
-
-#include <mlpack/core.hpp>
-/*
-This class is used to initialize the matrix
-weightVectors to zero.
-*/
-namespace mlpack {
-namespace perceptron {
- class ZeroInitialization
- {
- public:
- ZeroInitialization()
- { }
-
- inline static void initialize(arma::mat& W, size_t row, size_t col)
- {
- arma::mat tempWeights(row, col);
- tempWeights.fill(0.0);
-
- W = tempWeights;
- }
- }; // class ZeroInitialization
-}; // namespace perceptron
-}; // namespace mlpack
-
-#endif
\ No newline at end of file
diff --git a/src/mlpack/methods/perceptron/InitializationMethods/CMakeLists.txt b/src/mlpack/methods/perceptron/initialization_methods/CMakeLists.txt
similarity index 100%
rename from src/mlpack/methods/perceptron/InitializationMethods/CMakeLists.txt
rename to src/mlpack/methods/perceptron/initialization_methods/CMakeLists.txt
diff --git a/src/mlpack/methods/perceptron/initialization_methods/random_init.hpp b/src/mlpack/methods/perceptron/initialization_methods/random_init.hpp
new file mode 100644
index 0000000..f88e952
--- /dev/null
+++ b/src/mlpack/methods/perceptron/initialization_methods/random_init.hpp
@@ -0,0 +1,35 @@
+/**
+ * @file random_init.hpp
+ * @author Udit Saxena
+ *
+ * Random initialization for perceptron weights.
+ */
+#ifndef _MLPACK_METHOS_PERCEPTRON_INITIALIZATION_METHODS_RANDOM_INIT_HPP
+#define _MLPACK_METHOS_PERCEPTRON_INITIALIZATION_METHODS_RANDOM_INIT_HPP
+
+#include <mlpack/core.hpp>
+
+namespace mlpack {
+namespace perceptron {
+
+/**
+ * This class is used to initialize weights for the weightVectors matrix in a
+ * random manner.
+ */
+class RandomInitialization
+{
+ public:
+ RandomInitialization() { }
+
+ inline static void Initialize(arma::mat& W,
+ const size_t row,
+ const size_t col)
+ {
+ W = arma::randu<arma::mat>(row, col);
+ }
+}; // class RandomInitialization
+
+}; // namespace perceptron
+}; // namespace mlpack
+
+#endif
diff --git a/src/mlpack/methods/perceptron/initialization_methods/zero_init.hpp b/src/mlpack/methods/perceptron/initialization_methods/zero_init.hpp
new file mode 100644
index 0000000..0a02459
--- /dev/null
+++ b/src/mlpack/methods/perceptron/initialization_methods/zero_init.hpp
@@ -0,0 +1,37 @@
+/**
+ * @file zero_init.hpp
+ * @author Udit Saxena
+ *
+ * Implementation of ZeroInitialization policy for perceptrons.
+ */
+#ifndef _MLPACK_METHOS_PERCEPTRON_INITIALIZATION_METHODS_ZERO_INIT_HPP
+#define _MLPACK_METHOS_PERCEPTRON_INITIALIZATION_METHODS_ZERO_INIT_HPP
+
+#include <mlpack/core.hpp>
+
+namespace mlpack {
+namespace perceptron {
+
+/**
+ * This class is used to initialize the matrix weightVectors to zero.
+ */
+class ZeroInitialization
+{
+ public:
+ ZeroInitialization() { }
+
+ inline static void Initialize(arma::mat& W,
+ const size_t row,
+ const size_t col)
+ {
+ arma::mat tempWeights(row, col);
+ tempWeights.fill(0.0);
+
+ W = tempWeights;
+ }
+}; // class ZeroInitialization
+
+}; // namespace perceptron
+}; // namespace mlpack
+
+#endif
diff --git a/src/mlpack/methods/perceptron/LearnPolicy/CMakeLists.txt b/src/mlpack/methods/perceptron/learning_policies/CMakeLists.txt
similarity index 93%
rename from src/mlpack/methods/perceptron/LearnPolicy/CMakeLists.txt
rename to src/mlpack/methods/perceptron/learning_policies/CMakeLists.txt
index a07bc01..119239d 100644
--- a/src/mlpack/methods/perceptron/LearnPolicy/CMakeLists.txt
+++ b/src/mlpack/methods/perceptron/learning_policies/CMakeLists.txt
@@ -1,7 +1,7 @@
# Define the files we need to compile
# Anything not in this list will not be compiled into MLPACK.
set(SOURCES
- SimpleWeightUpdate.hpp
+ simple_weight_update.hpp
)
# Add directory name to sources.
diff --git a/src/mlpack/methods/perceptron/LearnPolicy/SimpleWeightUpdate.hpp b/src/mlpack/methods/perceptron/learning_policies/simple_weight_update.hpp
similarity index 100%
rename from src/mlpack/methods/perceptron/LearnPolicy/SimpleWeightUpdate.hpp
rename to src/mlpack/methods/perceptron/learning_policies/simple_weight_update.hpp
diff --git a/src/mlpack/methods/perceptron/perceptron.hpp b/src/mlpack/methods/perceptron/perceptron.hpp
index 7d26875..7842e35 100644
--- a/src/mlpack/methods/perceptron/perceptron.hpp
+++ b/src/mlpack/methods/perceptron/perceptron.hpp
@@ -1,86 +1,72 @@
-/*
- * @file: perceptron.hpp
- * @author: Udit Saxena
+/**
+ * @file perceptron.hpp
+ * @author Udit Saxena
*
- *
- * Definition of Perceptron
+ * Definition of Perceptron class.
*/
-
-#ifndef _MLPACK_METHODS_PERCEPTRON_HPP
-#define _MLPACK_METHODS_PERCEPTRON_HPP
+#ifndef __MLPACK_METHODS_PERCEPTRON_PERCEPTRON_HPP
+#define __MLPACK_METHODS_PERCEPTRON_PERCEPTRON_HPP
#include <mlpack/core.hpp>
-#include "InitializationMethods/zero_init.hpp"
-#include "InitializationMethods/random_init.hpp"
-#include "LearnPolicy/SimpleWeightUpdate.hpp"
+#include "initialization_methods/zero_init.hpp"
+#include "initialization_methods/random_init.hpp"
+#include "learning_policies/simple_weight_update.hpp"
namespace mlpack {
namespace perceptron {
-template <typename LearnPolicy = SimpleWeightUpdate,
- typename WeightInitializationPolicy = ZeroInitialization,
- typename MatType = arma::mat>
+/**
+ * This class implements a simple perceptron (i.e., a single layer neural
+ * network). It converges if the supplied training dataset is linearly
+ * separable.
+ *
+ * @tparam LearnPolicy Options of SimpleWeightUpdate and GradientDescent.
+ * @tparam WeightInitializationPolicy Option of ZeroInitialization and
+ * RandomInitialization.
+ */
+template<typename LearnPolicy = SimpleWeightUpdate,
+ typename WeightInitializationPolicy = ZeroInitialization,
+ typename MatType = arma::mat>
class Perceptron
{
- /*
- This class implements a simple perceptron i.e. a single layer
- neural network. It converges if the supplied training dataset is
- linearly separable.
-
- LearnPolicy: Options of SimpleWeightUpdate and GradientDescent.
- WeightInitializationPolicy: Option of ZeroInitialization and
- RandomInitialization.
- */
-public:
- /*
- Constructor - Constructs the perceptron. Or rather, builds the weightVectors
- matrix, which is later used in Classification.
- It adds a bias input vector of 1 to the input data to take care of the bias
- weights.
-
- @param: data - Input, training data.
- @param: labels - Labels of dataset.
- @param: iterations - maximum number of iterations the perceptron
- learn algorithm is to be run.
- */
+ public:
+ /**
+ * Constructor - constructs the perceptron by building the weightVectors
+ * matrix, which is later used in Classification. It adds a bias input vector
+ * of 1 to the input data to take care of the bias weights.
+ *
+ * @param data Input, training data.
+ * @param labels Labels of dataset.
+ * @param iterations Maximum number of iterations for the perceptron learning
+ * algorithm.
+ */
Perceptron(const MatType& data, const arma::Row<size_t>& labels, int iterations);
- /*
- Classification function. After training, use the weightVectors matrix to
- classify test, and put the predicted classes in predictedLabels.
-
- @param: test - testing data or data to classify.
- @param: predictedLabels - vector to store the predicted classes after
- classifying test
- */
+ /**
+ * Classification function. After training, use the weightVectors matrix to
+ * classify test, and put the predicted classes in predictedLabels.
+ *
+ * @param test Testing data or data to classify.
+ * @param predictedLabels Vector to store the predicted classes after
+ * classifying test.
+ */
void Classify(const MatType& test, arma::Row<size_t>& predictedLabels);
private:
-
- /* Stores the class labels for the input data*/
+ //! Stores the class labels for the input data.
arma::Row<size_t> classLabels;
- /* Stores the weight vectors for each of the input class labels. */
+ //! Stores the weight vectors for each of the input class labels.
arma::mat weightVectors;
- /* Stores the training data to be used later on in UpdateWeights.*/
+ //! Stores the training data to be used later on in UpdateWeights.
arma::mat trainData;
-
- /*
- This function is called by the constructor to update the weightVectors
- matrix. It decreases the weights of the incorrectly classified class while
- increasing the weight of the correct class it should have been classified to.
-
- @param: rowIndex - index of the row which has been incorrectly predicted.
- @param: labelIndex - index of the vector in trainData.
- @param: vectorIndex - index of the class which should have been predicted.
- */
- // void UpdateWeights(size_t rowIndex, size_t labelIndex, size_t vectorIndex);
};
+
} // namespace perceptron
} // namespace mlpack
-#include "perceptron_impl.cpp"
+#include "perceptron_impl.hpp"
#endif
diff --git a/src/mlpack/methods/perceptron/perceptron_impl.cpp b/src/mlpack/methods/perceptron/perceptron_impl.cpp
deleted file mode 100644
index b29c722..0000000
--- a/src/mlpack/methods/perceptron/perceptron_impl.cpp
+++ /dev/null
@@ -1,118 +0,0 @@
-/*
- * @file: perceptron_impl.hpp
- * @author: Udit Saxena
- *
- */
-
-#ifndef _MLPACK_METHODS_PERCEPTRON_IMPL_CPP
-#define _MLPACK_METHODS_PERCEPTRON_IMPL_CPP
-
-#include "perceptron.hpp"
-
-namespace mlpack {
-namespace perceptron {
-
-/*
- Constructor - Constructs the perceptron. Or rather, builds the weightVectors
- matrix, which is later used in Classification.
- It adds a bias input vector of 1 to the input data to take care of the bias
- weights.
-
- @param: data - Input, training data.
- @param: labels - Labels of dataset.
- @param: iterations - maximum number of iterations the perceptron
- learn algorithm is to be run.
-*/
-template <typename LearnPolicy, typename WeightInitializationPolicy, typename MatType>
-Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Perceptron(const MatType& data,
- const arma::Row<size_t>& labels, int iterations)
-{
- arma::Row<size_t> uniqueLabels = arma::unique(labels);
-
- WeightInitializationPolicy WIP;
- WIP.initialize(weightVectors, uniqueLabels.n_elem, data.n_rows + 1);
-
- // Start training.
- classLabels = labels;
-
- trainData = data;
- // inserting a row of 1's at the top of the training data set.
- MatType zOnes(1, data.n_cols);
- zOnes.fill(1);
- trainData.insert_rows(0, zOnes);
-
- int j, i = 0, converged = 0;
- size_t tempLabel;
- arma::uword maxIndexRow, maxIndexCol;
- double maxVal;
- arma::mat tempLabelMat;
-
- LearnPolicy LP;
-
- while ((i < iterations) && (!converged))
- {
- // This outer loop is for each iteration,
- // and we use the 'converged' variable for noting whether or not
- // convergence has been reached.
- i++;
- converged = 1;
-
- // Now this inner loop is for going through the dataset in each iteration
- for (j = 0; j < data.n_cols; j++)
- {
- // Multiplying for each variable and checking
- // whether the current weight vector correctly classifies this.
- tempLabelMat = weightVectors * trainData.col(j);
-
- maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
- maxVal *= 2;
- //checking whether prediction is correct.
- if(maxIndexRow != classLabels(0,j))
- {
- // due to incorrect prediction, convergence set to 0
- converged = 0;
- tempLabel = labels(0,j);
- // send maxIndexRow for knowing which weight to update,
- // send j to know the value of the vector to update it with.
- // send tempLabel to know the correct class
- LP.UpdateWeights(trainData, weightVectors, j, tempLabel, maxIndexRow);
- }
- }
- }
-}
-
-/*
- Classification function. After training, use the weightVectors matrix to
- classify test, and put the predicted classes in predictedLabels.
-
- @param: test - testing data or data to classify.
- @param: predictedLabels - vector to store the predicted classes after
- classifying test
- */
-template <typename LearnPolicy, typename WeightInitializationPolicy, typename MatType>
-void Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Classify(
- const MatType& test, arma::Row<size_t>& predictedLabels)
-{
- int i;
- arma::mat tempLabelMat;
- arma::uword maxIndexRow, maxIndexCol;
- double maxVal;
- MatType testData = test;
-
- MatType zOnes(1, test.n_cols);
- zOnes.fill(1);
- testData.insert_rows(0, zOnes);
-
- for (i = 0; i < test.n_cols; i++)
- {
- tempLabelMat = weightVectors * testData.col(i);
- maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
- maxVal *= 2;
- predictedLabels(0,i) = maxIndexRow;
- }
-}
-
-}; // namespace perceptron
-}; // namespace mlpack
-
-#endif
\ No newline at end of file
diff --git a/src/mlpack/methods/perceptron/perceptron_impl.hpp b/src/mlpack/methods/perceptron/perceptron_impl.hpp
new file mode 100644
index 0000000..cb63017
--- /dev/null
+++ b/src/mlpack/methods/perceptron/perceptron_impl.hpp
@@ -0,0 +1,122 @@
+/**
+ * @file perceptron_impl.hpp
+ * @author Udit Saxena
+ *
+ * Implementation of Perceptron class.
+ */
+#ifndef __MLPACK_METHODS_PERCEPTRON_PERCEPTRON_IMPL_HPP
+#define __MLPACK_METHODS_PERCEPTRON_PERCEPTRON_IMPL_HPP
+
+#include "perceptron.hpp"
+
+namespace mlpack {
+namespace perceptron {
+
+/**
+ * Constructor - constructs the perceptron. Or rather, builds the weightVectors
+ * matrix, which is later used in Classification.
+ * It adds a bias input vector of 1 to the input data to take care of the bias
+ * weights.
+ *
+ * @param data Input, training data.
+ * @param labels Labels of dataset.
+ * @param iterations Maximum number of iterations for the perceptron learning
+ * algorithm.
+ */
+template<
+ typename LearnPolicy,
+ typename WeightInitializationPolicy,
+ typename MatType
+>
+Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Perceptron(
+ const MatType& data,
+ const arma::Row<size_t>& labels,
+ int iterations)
+{
+ arma::Row<size_t> uniqueLabels = arma::unique(labels);
+
+ WeightInitializationPolicy WIP;
+ WIP.Initialize(weightVectors, uniqueLabels.n_elem, data.n_rows + 1);
+
+ // Start training.
+ classLabels = labels;
+
+ trainData = data;
+ // Insert a row of ones at the top of the training data set.
+ MatType zOnes(1, data.n_cols);
+ zOnes.fill(1);
+ trainData.insert_rows(0, zOnes);
+
+ int j, i = 0, converged = 0;
+ size_t tempLabel;
+ arma::uword maxIndexRow, maxIndexCol;
+ double maxVal;
+ arma::mat tempLabelMat;
+
+ LearnPolicy LP;
+
+ while ((i < iterations) && (!converged))
+ {
+ // This outer loop is for each iteration, and we use the 'converged'
+ // variable for noting whether or not convergence has been reached.
+ i++;
+ converged = 1;
+
+ // Now this inner loop is for going through the dataset in each iteration.
+ for (j = 0; j < data.n_cols; j++)
+ {
+ // Multiply for each variable and check whether the current weight vector
+ // correctly classifies this.
+ tempLabelMat = weightVectors * trainData.col(j);
+
+ maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
+ maxVal *= 2;
+ // Check whether prediction is correct.
+ if (maxIndexRow != classLabels(0, j))
+ {
+ // Due to incorrect prediction, convergence set to 0.
+ converged = 0;
+ tempLabel = labels(0, j);
+ // Send maxIndexRow for knowing which weight to update, send j to know
+ // the value of the vector to update it with. Send tempLabel to know
+ // the correct class.
+ LP.UpdateWeights(trainData, weightVectors, j, tempLabel, maxIndexRow);
+ }
+ }
+ }
+}
+
+/**
+ * Classification function. After training, use the weightVectors matrix to
+ * classify test, and put the predicted classes in predictedLabels.
+ *
+ * @param test testing data or data to classify.
+ * @param predictedLabels vector to store the predicted classes after
+ * classifying test
+ */
+template <typename LearnPolicy, typename WeightInitializationPolicy, typename MatType>
+void Perceptron<LearnPolicy, WeightInitializationPolicy, MatType>::Classify(
+ const MatType& test, arma::Row<size_t>& predictedLabels)
+{
+ arma::mat tempLabelMat;
+ arma::uword maxIndexRow, maxIndexCol;
+ double maxVal;
+ MatType testData = test;
+
+ MatType zOnes(1, test.n_cols);
+ zOnes.fill(1);
+ testData.insert_rows(0, zOnes);
+
+ for (int i = 0; i < test.n_cols; i++)
+ {
+ tempLabelMat = weightVectors * testData.col(i);
+ maxVal = tempLabelMat.max(maxIndexRow, maxIndexCol);
+ maxVal *= 2;
+ predictedLabels(0, i) = maxIndexRow;
+ }
+}
+
+}; // namespace perceptron
+}; // namespace mlpack
+
+#endif
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