#include <mlpack/core.hpp>#include <mlpack/methods/amf/amf.hpp>#include <mlpack/methods/amf/update_rules/svd_batch_learning.hpp>#include <mlpack/methods/amf/init_rules/random_init.hpp>#include <mlpack/methods/amf/init_rules/average_init.hpp>#include <mlpack/methods/amf/termination_policies/validation_rmse_termination.hpp>#include <mlpack/methods/amf/termination_policies/simple_tolerance_termination.hpp>#include "catch.hpp"
Include dependency graph for svd_batch_test.cpp:
Classes | |
| class | SpecificRandomInitialization |
| This is used to ensure we start from the same initial point. More... | |
Functions | |
| TEST_CASE ("SVDBatchConvergenceElementTest", "[SVDBatchTest]") | |
| Make sure the SVD Batch lerning is converging. | |
| TEST_CASE ("SVDBatchMomentumTest", "[SVDBatchTest]") | |
| Make sure the momentum is working okay. | |
| TEST_CASE ("SVDBatchRegularizationTest", "[SVDBatchTest]") | |
| Make sure the regularization is working okay. | |
| TEST_CASE ("SVDBatchNegativeElementTest", "[SVDBatchTest]") | |
| Make sure the SVD can factorize matrices with negative entries. | |
Detailed Description
Test the SVDBatchLearning class for AMF.
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