apaam/mlpack
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge pull request #14 from AYESDIE/AYESDIE-updated-test

Browse Source 
Updated cf_test.cpp
This commit is contained in:
AYESDIE
2018-11-09 14:37:59 +05:30
committed by GitHub
parent c8b24cceee 0a0ed35e05
commit ab02eb504d
1 changed files with 17 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
src/mlpack/tests/main_tests/cf_test.cpp
+17 -15
View File
@@ -476,7 +476,7 @@ BOOST_AUTO_TEST_CASE(CFInterpolationTest)
// Query with different interpolation types.
ResetSettings();
// Using average interplation algorithm.
// Using average interpolation algorithm.
SetInputParam("training", dataset);
SetInputParam("max_iterations", int(10));
SetInputParam("query", query);
@@ -490,11 +490,14 @@ BOOST_AUTO_TEST_CASE(CFInterpolationTest)
BOOST_REQUIRE_EQUAL(output1.n_rows, 5);
BOOST_REQUIRE_EQUAL(output1.n_cols, 7);
ResetSettings();
// Reset passed parameters.
CLI::GetSingleton().Parameters()["training"].wasPassed = false;
CLI::GetSingleton().Parameters()["max_iterations"].wasPassed = false;
CLI::GetSingleton().Parameters()["algorithm"].wasPassed = false;
// Using regression interpolation algorithm.
SetInputParam("training", dataset);
SetInputParam("max_iterations", int(10));
SetInputParam("input_model",
std::move(CLI::GetParam<CFModel*>("output_model")));
SetInputParam("query", query);
SetInputParam("interpolation", std::string("regression"));
SetInputParam("recommendations", 5);
@@ -506,11 +509,9 @@ BOOST_AUTO_TEST_CASE(CFInterpolationTest)
BOOST_REQUIRE_EQUAL(output2.n_rows, 5);
BOOST_REQUIRE_EQUAL(output2.n_cols, 7);
ResetSettings();
// Using similarity interpolation algorithm.
SetInputParam("training", dataset);
SetInputParam("max_iterations", int(10));
SetInputParam("input_model",
std::move(CLI::GetParam<CFModel*>("output_model")));
SetInputParam("query", query);
SetInputParam("interpolation", std::string("similarity"));
SetInputParam("recommendations", 5);
@@ -577,11 +578,14 @@ BOOST_AUTO_TEST_CASE(CFNeighborSearchTest)
BOOST_REQUIRE_EQUAL(output1.n_rows, 5);
BOOST_REQUIRE_EQUAL(output1.n_cols, 7);
ResetSettings();
// Reset passed parameters.
CLI::GetSingleton().Parameters()["training"].wasPassed = false;
CLI::GetSingleton().Parameters()["max_iterations"].wasPassed = false;
CLI::GetSingleton().Parameters()["algorithm"].wasPassed = false;
// Using cosine neighbor search algorithm.
SetInputParam("training", dataset);
SetInputParam("max_iterations", int(10));
SetInputParam("input_model",
std::move(CLI::GetParam<CFModel*>("output_model")));
SetInputParam("query", query);
SetInputParam("neighbor_search", std::string("cosine"));
SetInputParam("recommendations", 5);
@@ -593,11 +597,9 @@ BOOST_AUTO_TEST_CASE(CFNeighborSearchTest)
BOOST_REQUIRE_EQUAL(output2.n_rows, 5);
BOOST_REQUIRE_EQUAL(output2.n_cols, 7);
ResetSettings();
// Using pearson neighbor search algorithm.
SetInputParam("training", dataset);
SetInputParam("max_iterations", int(10));
SetInputParam("input_model",
std::move(CLI::GetParam<CFModel*>("output_model")));
SetInputParam("query", query);
SetInputParam("neighbor_search", std::string("pearson"));
SetInputParam("recommendations", 5);