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fix to tests

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This commit is contained in:
Ayush
2019-04-07 22:05:07 -04:00
committed by Ryan Curtin
parent 59c8575a8d
commit 6dc5665936
1 changed files with 24 additions and 24 deletions
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src/mlpack/tests/linear_svm_test.cpp
+24 -24
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@@ -46,7 +46,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionEvaluate)
BOOST_REQUIRE_CLOSE(svmf.Evaluate(parameters), 1.0, 1e-5);
parameters = "2 0 1 2 2;"
" 1 2 2 2 2";
"1 2 2 2 2";
BOOST_REQUIRE_CLOSE(svmf.Evaluate(parameters), 2.0, 1e-5);
parameters = "-0.1425 8.3228 0.1724 -0.3374 0.1548;"
@@ -69,7 +69,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionEvaluate)
BOOST_AUTO_TEST_CASE(LinearSVMFunctionRandomBinaryEvaluate)
{
const size_t points = 1000;
const size_t trials = 25;
const size_t trials = 10;
const size_t inputSize = 10;
const size_t numClasses = 2;
@@ -123,8 +123,8 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionRandomBinaryEvaluate)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionRandomEvaluate)
{
const size_t points = 1000;
const size_t trials = 25;
const size_t points = 500;
const size_t trials = 10;
const size_t inputSize = 10;
const size_t numClasses = 5;
@@ -178,8 +178,8 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionRandomEvaluate)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionRegularizationEvaluate)
{
const size_t points = 1000;
const size_t trials = 25;
const size_t points = 500;
const size_t trials = 10;
const size_t inputSize = 10;
const size_t numClasses = 3;
@@ -224,8 +224,8 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionRegularizationEvaluate)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionSeparableEvaluate)
{
const size_t points = 1000;
const size_t trials = 25;
const size_t points = 500;
const size_t trials = 10;
const size_t inputSize = 10;
const size_t numClasses = 3;
@@ -264,8 +264,8 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionSeparableEvaluate)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionRegularizationSeparableEvaluate)
{
const size_t points = 500;
const size_t trials = 10;
const size_t points = 100;
const size_t trials = 3;
const size_t inputSize = 10;
const size_t numClasses = 3;
@@ -317,7 +317,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionRegularizationSeparableEvaluate)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionGradient)
{
const size_t points = 1000;
const size_t points = 500;
const size_t inputSize = 10;
const size_t numClasses = 3;
@@ -373,8 +373,8 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionGradient)
parameters(i, j) += epsilon;
// Compare numerical and backpropagation gradient values.
BOOST_REQUIRE_CLOSE(numGradient1, gradient1(i, j), 1e-5);
BOOST_REQUIRE_CLOSE(numGradient2, gradient2(i, j), 1e-5);
BOOST_REQUIRE_SMALL(numGradient1 - gradient1(i, j), 1e-2);
BOOST_REQUIRE_SMALL(numGradient2 - gradient2(i, j), 1e-2);
}
}
}
@@ -385,10 +385,10 @@ BOOST_AUTO_TEST_CASE(LinearSVMFunctionGradient)
*/
BOOST_AUTO_TEST_CASE(LinearSVMFunctionSeparableGradient)
{
const size_t points = 1000;
const size_t points = 100;
const size_t trials = 3;
const size_t inputSize = 10;
const size_t numClasses = 3;
const size_t inputSize = 5;
const size_t numClasses = 5;
// Initialize a random dataset.
arma::mat data;
@@ -457,7 +457,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMPSGDSimpleTest)
// Create a linear svm object using a custom Parallel
// SGD object.
ens::ParallelSGD<> psgd(500000, 3, 1e-5);
ens::ParallelSGD<> psgd(1000, 3, 1e-5);
LinearSVM<arma::mat> lsvm(dataset, labels, 2, 0.0001, psgd);
// Compare training accuracy to 100.
@@ -519,7 +519,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMPSGDTwoClasses)
}
// Train linear svm object using Parallel SGD optimizer.
ens::ParallelSGD<> psgd(1000, 1000, 1e-5);
ens::ParallelSGD<> psgd(1000, 500, 1e-5);
LinearSVM<arma::mat> lsvm(data, labels, numClasses, lambda, psgd);
// Compare training accuracy to 100.
@@ -549,7 +549,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMPSGDTwoClasses)
*/
BOOST_AUTO_TEST_CASE(LinearSVMLBFGSTwoClasses)
{
const size_t points = 1000;
const size_t points = 500;
const size_t inputSize = 3;
const size_t numClasses = 2;
const double lambda = 0.5;
@@ -624,7 +624,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMSparseLBFGSTest)
*/
BOOST_AUTO_TEST_CASE(LinearSVMLBFGSMultipleClasses)
{
const size_t points = 5000;
const size_t points = 500;
const size_t inputSize = 5;
const size_t numClasses = 5;
const double lambda = 0.5;
@@ -742,7 +742,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMTrainTest)
*/
BOOST_AUTO_TEST_CASE(LinearSVMClassifySinglePointTest)
{
const size_t points = 1000;
const size_t points = 500;
const size_t inputSize = 5;
const size_t numClasses = 5;
const double lambda = 0.5;
@@ -827,7 +827,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMClassifySinglePointTest)
*/
BOOST_AUTO_TEST_CASE(LinearSVMClassifyTest)
{
const size_t points = 1000;
const size_t points = 500;
const size_t inputSize = 5;
const size_t numClasses = 5;
const double lambda = 0.5;
@@ -902,7 +902,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMClassifyTest)
arma::Row<size_t> predictions;
lsvm.Classify(data, predictions);
BOOST_REQUIRE_GE((double) arma::accu(predictions == labels), 900);
BOOST_REQUIRE_GE((double) arma::accu(predictions == labels), 450);
}
/**
@@ -911,7 +911,7 @@ BOOST_AUTO_TEST_CASE(LinearSVMClassifyTest)
*/
BOOST_AUTO_TEST_CASE(SinglePointClassifyTest)
{
const size_t points = 1000;
const size_t points = 500;
const size_t inputSize = 5;
const size_t numClasses = 5;
const double lambda = 0.5;