[mlpack] 149/149: Tests for Non-linearly separable dataset fixed.

[Barak A. Pearlmutter]

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

commit 35183840f52ed256e192ea6b9a3d6fc3bbe4ea79
Author: saxena.udit <saxena.udit at 9d5b8971-822b-0410-80eb-d18c1038ef23>
Date:   Wed Jan 7 20:04:08 2015 +0000

    Tests for Non-linearly separable dataset fixed.
    
    git-svn-id: http://svn.cc.gatech.edu/fastlab/mlpack/trunk@17507 9d5b8971-822b-0410-80eb-d18c1038ef23
---
 src/mlpack/tests/adaboost_test.cpp | 55 +++-----------------------------------
 1 file changed, 4 insertions(+), 51 deletions(-)

diff --git a/src/mlpack/tests/adaboost_test.cpp b/src/mlpack/tests/adaboost_test.cpp
index 8c526d7..6d0ec63 100644
--- a/src/mlpack/tests/adaboost_test.cpp
+++ b/src/mlpack/tests/adaboost_test.cpp
@@ -207,15 +207,10 @@ BOOST_AUTO_TEST_CASE(HammingLossBoundNonLinearSepData)
 
   arma::Mat<size_t> labels;
 
-<<<<<<< HEAD
-  if (!data::Load("nonlinsepdata_labels.txt", labels))
-    BOOST_FAIL("Cannot load labels for nonlinsepdata_labels.txt");
 
-=======
   if (!data::Load("train_labels_nonlinsep.txt",labels))
     BOOST_FAIL("Cannot load labels for train_labels_nonlinsep.txt");
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
   // no need to map the labels here
 
   // Define your own weak learner, perceptron in this case.
@@ -254,15 +249,9 @@ BOOST_AUTO_TEST_CASE(WeakLearnerErrorNonLinearSepData)
 
   arma::Mat<size_t> labels;
 
-<<<<<<< HEAD
-  if (!data::Load("nonlinsepdata_labels.txt",labels))
-    BOOST_FAIL("Cannot load labels for nonlinsepdata_labels.txt");
-
-=======
   if (!data::Load("train_labels_nonlinsep.txt",labels))
     BOOST_FAIL("Cannot load labels for train_labels_nonlinsep.txt");
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
   // no need to map the labels here
 
   // Define your own weak learner, perceptron in this case.
@@ -501,15 +490,10 @@ BOOST_AUTO_TEST_CASE(HammingLossBoundNonLinearSepData_DS)
 
   arma::Mat<size_t> labels;
 
-<<<<<<< HEAD
-  if (!data::Load("nonlinsepdata_labels.txt",labels))
-    BOOST_FAIL("Cannot load labels for nonlinsepdata_labels.txt");
-
-=======
   if (!data::Load("train_labels_nonlinsep.txt",labels))
     BOOST_FAIL("Cannot load labels for train_labels_nonlinsep.txt");
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
+
   // no need to map the labels here
 
   // Define your own weak learner, Decision Stump in this case.
@@ -553,15 +537,9 @@ BOOST_AUTO_TEST_CASE(WeakLearnerErrorNonLinearSepData_DS)
 
   arma::Mat<size_t> labels;
 
-<<<<<<< HEAD
-  if (!data::Load("nonlinsepdata_labels.txt",labels))
-    BOOST_FAIL("Cannot load labels for nonlinsepdata_labels.txt");
-
-=======
   if (!data::Load("train_labels_nonlinsep.txt",labels))
     BOOST_FAIL("Cannot load labels for train_labels_nonlinsep.txt");
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
   // no need to map the labels here
 
   // Define your own weak learner, Decision Stump in this case.
@@ -617,9 +595,7 @@ BOOST_AUTO_TEST_CASE(ClassifyTest_VERTEBRALCOL)
 
   // Define your own weak learner, perceptron in this case.
   // Run the perceptron for perceptron_iter iterations.
-<<<<<<< HEAD
-  int perceptron_iter = 5000;
-=======
+
   int perceptron_iter = 1000;
   
   arma::mat testData;
@@ -631,43 +607,30 @@ BOOST_AUTO_TEST_CASE(ClassifyTest_VERTEBRALCOL)
 
   if (!data::Load("vc2_test_labels.txt",trueTestLabels))
     BOOST_FAIL("Cannot load labels for vc2_test_labels.txt");
->>>>>>> Tests for Non-linearly separable dataset fixed.
 
   arma::Row<size_t> perceptronPrediction(labels.n_cols);
   perceptron::Perceptron<> p(inputData, labels.row(0), perceptron_iter);
   p.Classify(inputData, perceptronPrediction);
 
   // Define parameters for the adaboost
-<<<<<<< HEAD
-  int iterations = 250;
-  double tolerance = 1e-10;
-  AdaBoost<> a(inputData, labels.row(0), iterations, tolerance, p);
 
-  arma::Row<size_t> predictedLabels(inputData.n_cols);
-  a.Classify(inputData, predictedLabels);
-=======
   int iterations = 100;
   double tolerance = 1e-10;
   AdaBoost<> a(inputData, labels.row(0), iterations, tolerance, p);
   
   arma::Row<size_t> predictedLabels(testData.n_cols);
   a.Classify(testData, predictedLabels);
->>>>>>> Tests for Non-linearly separable dataset fixed.
 
   int localError = 0;
   
   for (size_t i = 0; i < trueTestLabels.n_cols; i++)
     if(trueTestLabels(i) != predictedLabels(i))
       localError++;
-<<<<<<< HEAD
-  double lError = (double) localError / labels.n_cols;
-
-  BOOST_REQUIRE_LT(lError, 0.30);
-=======
+  
   double lError = (double) localError / trueTestLabels.n_cols;
   
   BOOST_REQUIRE(lError <= 0.30);
->>>>>>> Tests for Non-linearly separable dataset fixed.
+
 }
 
 /**
@@ -684,15 +647,9 @@ BOOST_AUTO_TEST_CASE(ClassifyTest_NONLINSEP)
 
   arma::Mat<size_t> labels;
 
-<<<<<<< HEAD
-  if (!data::Load("nonlinsepdata_labels.txt",labels))
-    BOOST_FAIL("Cannot load labels for nonlinsepdata_labels.txt");
-
-=======
   if (!data::Load("train_labels_nonlinsep.txt",labels))
     BOOST_FAIL("Cannot load labels for train_labels_nonlinsep.txt");
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
   // no need to map the labels here
 
   // Define your own weak learner, perceptron in this case.
@@ -729,13 +686,9 @@ BOOST_AUTO_TEST_CASE(ClassifyTest_NONLINSEP)
   for (size_t i = 0; i < trueTestLabels.n_cols; i++)
     if(trueTestLabels(i) != predictedLabels(i))
       localError++;
-<<<<<<< HEAD
-  double lError = (double) localError / labels.n_cols;
 
-=======
   double lError = (double) localError / trueTestLabels.n_cols;
   
->>>>>>> Tests for Non-linearly separable dataset fixed.
   BOOST_REQUIRE(lError <= 0.30);
 }
 

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