[mlpack] 229/324: New tests added for adaboost.

Barak A. Pearlmutter barak+git at cs.nuim.ie
Sun Aug 17 08:22:13 UTC 2014


This is an automated email from the git hooks/post-receive script.

bap pushed a commit to branch svn-trunk
in repository mlpack.

commit 2b32e08a4f34678d14135903f70f00d262de960d
Author: saxena.udit <saxena.udit at 9d5b8971-822b-0410-80eb-d18c1038ef23>
Date:   Sun Jul 27 19:37:49 2014 +0000

    New tests added for adaboost.
    
    git-svn-id: http://svn.cc.gatech.edu/fastlab/mlpack/trunk@16875 9d5b8971-822b-0410-80eb-d18c1038ef23
---
 src/mlpack/methods/adaboost/adaboost_impl.hpp |  18 +-
 src/mlpack/tests/adaboost_test.cpp            | 134 ++++++++++-
 src/mlpack/tests/data/vc2.txt                 | 310 ++++++++++++++++++++++++++
 src/mlpack/tests/data/vc2_labels.txt          | 310 ++++++++++++++++++++++++++
 4 files changed, 769 insertions(+), 3 deletions(-)

diff --git a/src/mlpack/methods/adaboost/adaboost_impl.hpp b/src/mlpack/methods/adaboost/adaboost_impl.hpp
index b39d229..3d0d663 100644
--- a/src/mlpack/methods/adaboost/adaboost_impl.hpp
+++ b/src/mlpack/methods/adaboost/adaboost_impl.hpp
@@ -53,7 +53,11 @@ Adaboost<MatType, WeakLearner>::Adaboost(const MatType& data,
   size_t numClasses = (arma::max(labels) - arma::min(labels)) + 1;
 
   int i, j, k;
-  double rt, alphat = 0.0, zt;
+  double rt, crt, alphat = 0.0, zt;
+  double tolerance = 1e-20;
+  // std::cout<<"Tolerance is "<<tolerance<<"\n";
+  // crt is for stopping the iterations when rt 
+  // stops changing by less than a tolerant value.
   
   ztAccumulator = 1.0; 
   
@@ -94,6 +98,7 @@ Adaboost<MatType, WeakLearner>::Adaboost(const MatType& data,
   // now start the boosting rounds
   for (i = 0; i < iterations; i++)
   {
+    // std::cout<<"Run "<<i<<" times.\n";
     // Initialized to zero in every round.
     rt = 0.0; 
     zt = 0.0;
@@ -118,6 +123,17 @@ Adaboost<MatType, WeakLearner>::Adaboost(const MatType& data,
         rt += (D(j,k) * yt(j,k) * ht(j,k));
     }
     // end calculation of rt
+    // std::cout<<"Value of rt is: "<<rt<<"\n";
+
+    if (i > 0)
+    {
+      if ( (rt - crt) < tolerance)
+      {
+        // std::cout<<(rt-crt)<<"\n";
+        i = iterations;
+      }
+    }
+    crt = rt;
 
     alphat = 0.5 * log((1 + rt) / (1 - rt));
     // end calculation of alphat
diff --git a/src/mlpack/tests/adaboost_test.cpp b/src/mlpack/tests/adaboost_test.cpp
index 880c678..d613e21 100644
--- a/src/mlpack/tests/adaboost_test.cpp
+++ b/src/mlpack/tests/adaboost_test.cpp
@@ -22,7 +22,7 @@ BOOST_AUTO_TEST_SUITE(AdaboostTest);
  *  It checks whether the hamming loss breaches the upperbound, which
  *  is provided by ztAccumulator.
  */
-BOOST_AUTO_TEST_CASE(HammingLossBound)
+BOOST_AUTO_TEST_CASE(HammingLossBoundIris)
 {
   arma::mat inputData;
 
@@ -38,7 +38,7 @@ BOOST_AUTO_TEST_CASE(HammingLossBound)
 
   // Define your own weak learner, perceptron in this case.
   // Run the perceptron for perceptron_iter iterations.
-  int perceptron_iter = 4000;
+  int perceptron_iter = 400;
 
   perceptron::Perceptron<> p(inputData, labels.row(0), perceptron_iter);
 
@@ -54,4 +54,134 @@ BOOST_AUTO_TEST_CASE(HammingLossBound)
   BOOST_REQUIRE(hammingLoss <= a.ztAccumulator);
 }
 
+/**
+ *  This test case runs the Adaboost.mh algorithm on the UCI Iris dataset.
+ *  It checks if the error returned by running a single instance of the 
+ *  weak learner is worse than running the boosted weak learner using 
+ *  adaboost.
+ */
+BOOST_AUTO_TEST_CASE(WeakLearnerErrorIris)
+{
+  arma::mat inputData;
+
+  if (!data::Load("iris.txt", inputData))
+    BOOST_FAIL("Cannot load test dataset iris.txt!");
+
+  arma::Mat<size_t> labels;
+
+  if (!data::Load("iris_labels.txt",labels))
+    BOOST_FAIL("Cannot load labels for iris iris_labels.txt");
+  
+  // no need to map the labels here
+
+  // Define your own weak learner, perceptron in this case.
+  // Run the perceptron for perceptron_iter iterations.
+  int perceptron_iter = 400;
+
+  arma::Row<size_t> perceptronPrediction(labels.n_cols);
+  perceptron::Perceptron<> p(inputData, labels.row(0), perceptron_iter);
+  p.Classify(inputData, perceptronPrediction);
+  
+  int countWeakLearnerError = 0;
+  for (size_t i = 0; i < labels.n_cols; i++)
+    if(labels(i) != perceptronPrediction(i))
+      countWeakLearnerError++;
+  double weakLearnerErrorRate = (double) countWeakLearnerError / labels.n_cols;
+
+  // Define parameters for the adaboost
+  int iterations = 100;
+  Adaboost<> a(inputData, labels.row(0), iterations, p);
+  int countError = 0;
+  for (size_t i = 0; i < labels.n_cols; i++)
+    if(labels(i) != a.finalHypothesis(i))
+      countError++;
+  double error = (double) countError / labels.n_cols;
+
+  BOOST_REQUIRE(error <= weakLearnerErrorRate);
+}
+
+/**
+ *  This test case runs the Adaboost.mh algorithm on the UCI Vertebral 
+ *  Column dataset.
+ *  It checks whether the hamming loss breaches the upperbound, which
+ *  is provided by ztAccumulator.
+ */
+BOOST_AUTO_TEST_CASE(HammingLossBoundVertebralColumn)
+{
+  arma::mat inputData;
+
+  if (!data::Load("vc2.txt", inputData))
+    BOOST_FAIL("Cannot load test dataset vc2.txt!");
+
+  arma::Mat<size_t> labels;
+
+  if (!data::Load("vc2_labels.txt",labels))
+    BOOST_FAIL("Cannot load labels for vc2_labels.txt");
+  
+  // no need to map the labels here
+
+  // Define your own weak learner, perceptron in this case.
+  // Run the perceptron for perceptron_iter iterations.
+  int perceptron_iter = 800;
+
+  perceptron::Perceptron<> p(inputData, labels.row(0), perceptron_iter);
+
+  // Define parameters for the adaboost
+  int iterations = 50;
+  Adaboost<> a(inputData, labels.row(0), iterations, p);
+  int countError = 0;
+  for (size_t i = 0; i < labels.n_cols; i++)
+    if(labels(i) != a.finalHypothesis(i))
+      countError++;
+  double hammingLoss = (double) countError / labels.n_cols;
+
+  BOOST_REQUIRE(hammingLoss <= a.ztAccumulator);
+}
+
+/**
+ *  This test case runs the Adaboost.mh algorithm on the UCI Vertebral 
+ *  Column dataset.
+ *  It checks if the error returned by running a single instance of the 
+ *  weak learner is worse than running the boosted weak learner using 
+ *  adaboost.
+ */
+BOOST_AUTO_TEST_CASE(WeakLearnerErrorVertebralColumn)
+{
+  arma::mat inputData;
+
+  if (!data::Load("vc2.txt", inputData))
+    BOOST_FAIL("Cannot load test dataset vc2.txt!");
+
+  arma::Mat<size_t> labels;
+
+  if (!data::Load("vc2_labels.txt",labels))
+    BOOST_FAIL("Cannot load labels for vc2_labels.txt");
+  
+  // no need to map the labels here
+
+  // Define your own weak learner, perceptron in this case.
+  // Run the perceptron for perceptron_iter iterations.
+  int perceptron_iter = 800;
+
+  arma::Row<size_t> perceptronPrediction(labels.n_cols);
+  perceptron::Perceptron<> p(inputData, labels.row(0), perceptron_iter);
+  p.Classify(inputData, perceptronPrediction);
+  
+  int countWeakLearnerError = 0;
+  for (size_t i = 0; i < labels.n_cols; i++)
+    if(labels(i) != perceptronPrediction(i))
+      countWeakLearnerError++;
+  double weakLearnerErrorRate = (double) countWeakLearnerError / labels.n_cols;
+
+  // Define parameters for the adaboost
+  int iterations = 50;
+  Adaboost<> a(inputData, labels.row(0), iterations, p);
+  int countError = 0;
+  for (size_t i = 0; i < labels.n_cols; i++)
+    if(labels(i) != a.finalHypothesis(i))
+      countError++;
+  double error = (double) countError / labels.n_cols;
+  
+  BOOST_REQUIRE(error <= weakLearnerErrorRate);
+}
 BOOST_AUTO_TEST_SUITE_END();
\ No newline at end of file
diff --git a/src/mlpack/tests/data/vc2.txt b/src/mlpack/tests/data/vc2.txt
new file mode 100644
index 0000000..a181337
--- /dev/null
+++ b/src/mlpack/tests/data/vc2.txt
@@ -0,0 +1,310 @@
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+39.06	10.06	25.02	29	114.41	4.56
+68.83	22.22	50.09	46.61	105.99	-3.53
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+40.25	13.92	25.12	26.33	130.33	2.23
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+45.37	10.76	29.04	34.61	117.27	-10.68
+43.79	13.53	42.69	30.26	125	13.29
+36.69	5.01	41.95	31.68	84.24	0.66
+49.71	13.04	31.33	36.67	108.65	-7.83
+31.23	17.72	15.5	13.52	120.06	0.5
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+38.7	13.44	31	25.25	123.16	1.43
+41.73	12.25	30.12	29.48	116.59	-1.24
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+49	13.11	51.87	35.88	126.4	0.54
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+66.51	20.9	31.73	45.61	128.9	1.52
+82.91	29.89	58.25	53.01	110.71	6.08
+50.68	6.46	35	44.22	116.59	-0.21
+89.01	26.08	69.02	62.94	111.48	6.06
+54.6	21.49	29.36	33.11	118.34	-1.47
+34.38	2.06	32.39	32.32	128.3	-3.37
+45.08	12.31	44.58	32.77	147.89	-8.94
+47.9	13.62	36	34.29	117.45	-4.25
+53.94	20.72	29.22	33.22	114.37	-0.42
+61.45	22.69	46.17	38.75	125.67	-2.71
+45.25	8.69	41.58	36.56	118.55	0.21
+33.84	5.07	36.64	28.77	123.95	-0.2
diff --git a/src/mlpack/tests/data/vc2_labels.txt b/src/mlpack/tests/data/vc2_labels.txt
new file mode 100644
index 0000000..7601f70
--- /dev/null
+++ b/src/mlpack/tests/data/vc2_labels.txt
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-- 
Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/debian-science/packages/mlpack.git



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