[mlpack-git] master: Reorder template parameters for consistency. (782e446)
gitdub at big.cc.gt.atl.ga.us
gitdub at big.cc.gt.atl.ga.us
Fri Dec 11 12:46:50 EST 2015
Repository : https://github.com/mlpack/mlpack
On branch : master
Link : https://github.com/mlpack/mlpack/compare/dd7c8b93fe5f299cb534cda70c1c786456f9a78f...3b926fd86ab143eb8af7327b9fb89fead7538df0
>---------------------------------------------------------------
commit 782e446a44a4d17059361cd43f2066d46c6ce497
Author: Ryan Curtin <ryan at ratml.org>
Date: Fri Dec 11 02:51:56 2015 +0000
Reorder template parameters for consistency.
>---------------------------------------------------------------
782e446a44a4d17059361cd43f2066d46c6ce497
src/mlpack/methods/adaboost/adaboost.hpp | 4 ++--
src/mlpack/methods/adaboost/adaboost_impl.hpp | 20 ++++++++++----------
src/mlpack/tests/adaboost_test.cpp | 20 ++++++++++----------
3 files changed, 22 insertions(+), 22 deletions(-)
diff --git a/src/mlpack/methods/adaboost/adaboost.hpp b/src/mlpack/methods/adaboost/adaboost.hpp
index 678831b..d044951 100644
--- a/src/mlpack/methods/adaboost/adaboost.hpp
+++ b/src/mlpack/methods/adaboost/adaboost.hpp
@@ -71,8 +71,8 @@ namespace adaboost {
* @tparam MatType Data matrix type (i.e. arma::mat or arma::sp_mat).
* @tparam WeakLearnerType Type of weak learner to use.
*/
-template<typename MatType = arma::mat,
- typename WeakLearnerType = mlpack::perceptron::Perceptron<> >
+template<typename WeakLearnerType = mlpack::perceptron::Perceptron<>,
+ typename MatType = arma::mat>
class AdaBoost
{
public:
diff --git a/src/mlpack/methods/adaboost/adaboost_impl.hpp b/src/mlpack/methods/adaboost/adaboost_impl.hpp
index ee400e0..9800255 100644
--- a/src/mlpack/methods/adaboost/adaboost_impl.hpp
+++ b/src/mlpack/methods/adaboost/adaboost_impl.hpp
@@ -35,8 +35,8 @@ namespace adaboost {
* @param tol Tolerance for termination of Adaboost.MH.
* @param other Weak Learner, which has been initialized already.
*/
-template<typename MatType, typename WeakLearnerType>
-AdaBoost<MatType, WeakLearnerType>::AdaBoost(
+template<typename WeakLearnerType, typename MatType>
+AdaBoost<WeakLearnerType, MatType>::AdaBoost(
const MatType& data,
const arma::Row<size_t>& labels,
const WeakLearnerType& other,
@@ -47,16 +47,16 @@ AdaBoost<MatType, WeakLearnerType>::AdaBoost(
}
// Empty constructor.
-template<typename MatType, typename WeakLearnerType>
-AdaBoost<MatType, WeakLearnerType>::AdaBoost(const double tolerance) :
+template<typename WeakLearnerType, typename MatType>
+AdaBoost<WeakLearnerType, MatType>::AdaBoost(const double tolerance) :
tolerance(tolerance)
{
// Nothing to do.
}
// Train AdaBoost.
-template<typename MatType, typename WeakLearnerType>
-void AdaBoost<MatType, WeakLearnerType>::Train(
+template<typename WeakLearnerType, typename MatType>
+void AdaBoost<WeakLearnerType, MatType>::Train(
const MatType& data,
const arma::Row<size_t>& labels,
const WeakLearnerType& other,
@@ -188,8 +188,8 @@ void AdaBoost<MatType, WeakLearnerType>::Train(
/**
* Classify the given test points.
*/
-template<typename MatType, typename WeakLearnerType>
-void AdaBoost<MatType, WeakLearnerType>::Classify(
+template<typename WeakLearnerType, typename MatType>
+void AdaBoost<WeakLearnerType, MatType>::Classify(
const MatType& test,
arma::Row<size_t>& predictedLabels)
{
@@ -221,9 +221,9 @@ void AdaBoost<MatType, WeakLearnerType>::Classify(
/**
* Serialize the AdaBoost model.
*/
-template<typename MatType, typename WeakLearnerType>
+template<typename WeakLearnerType, typename MatType>
template<typename Archive>
-void AdaBoost<MatType, WeakLearnerType>::Serialize(Archive& ar,
+void AdaBoost<WeakLearnerType, MatType>::Serialize(Archive& ar,
const unsigned int /* version */)
{
ar & data::CreateNVP(classes, "classes");
diff --git a/src/mlpack/tests/adaboost_test.cpp b/src/mlpack/tests/adaboost_test.cpp
index 829438e..c22b521 100644
--- a/src/mlpack/tests/adaboost_test.cpp
+++ b/src/mlpack/tests/adaboost_test.cpp
@@ -300,7 +300,7 @@ BOOST_AUTO_TEST_CASE(HammingLossIris_DS)
// Define parameters for AdaBoost.
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -352,7 +352,7 @@ BOOST_AUTO_TEST_CASE(WeakLearnerErrorIris_DS)
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -393,7 +393,7 @@ BOOST_AUTO_TEST_CASE(HammingLossBoundVertebralColumn_DS)
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -441,7 +441,7 @@ BOOST_AUTO_TEST_CASE(WeakLearnerErrorVertebralColumn_DS)
// Define parameters for AdaBoost.
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<>> a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -481,7 +481,7 @@ BOOST_AUTO_TEST_CASE(HammingLossBoundNonLinearSepData_DS)
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -530,7 +530,7 @@ BOOST_AUTO_TEST_CASE(WeakLearnerErrorNonLinearSepData_DS)
size_t iterations = 500;
double tolerance = 1e-23;
- AdaBoost<mat, DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels;
@@ -633,7 +633,7 @@ BOOST_AUTO_TEST_CASE(ClassifyTest_NONLINSEP)
// Define parameters for AdaBoost.
size_t iterations = 50;
double tolerance = 1e-10;
- AdaBoost<mat, DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
+ AdaBoost<DecisionStump<> > a(inputData, labels.row(0), ds, iterations,
tolerance);
arma::Row<size_t> predictedLabels(testData.n_cols);
@@ -822,7 +822,7 @@ BOOST_AUTO_TEST_CASE(DecisionStumpSerializationTest)
labels[i] = 1;
DecisionStump<> p(data, labels, 2, 800);
- AdaBoost<mat, DecisionStump<>> ab(data, labels, p, 50, 1e-10);
+ AdaBoost<DecisionStump<>> ab(data, labels, p, 50, 1e-10);
// Now create another dataset to train with.
mat otherData = randu<mat>(5, 200);
@@ -835,9 +835,9 @@ BOOST_AUTO_TEST_CASE(DecisionStumpSerializationTest)
otherLabels[i] = 2;
DecisionStump<> p2(otherData, otherLabels, 3, 500);
- AdaBoost<mat, DecisionStump<>> abText(otherData, otherLabels, p2, 50, 1e-10);
+ AdaBoost<DecisionStump<>> abText(otherData, otherLabels, p2, 50, 1e-10);
- AdaBoost<mat, DecisionStump<>> abXml, abBinary;
+ AdaBoost<DecisionStump<>> abXml, abBinary;
SerializeObjectAll(ab, abXml, abText, abBinary);
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