[mlpack-svn] r16023 - mlpack/trunk/src/mlpack/tests
fastlab-svn at coffeetalk-1.cc.gatech.edu
fastlab-svn at coffeetalk-1.cc.gatech.edu
Wed Nov 13 13:02:31 EST 2013
Author: rcurtin
Date: Wed Nov 13 13:02:30 2013
New Revision: 16023
Log:
Add a randomized test for the logistic regression likelihood function that is
not just comprised of simple examples.
Modified:
mlpack/trunk/src/mlpack/tests/logistic_regression_test.cpp
Modified: mlpack/trunk/src/mlpack/tests/logistic_regression_test.cpp
==============================================================================
--- mlpack/trunk/src/mlpack/tests/logistic_regression_test.cpp (original)
+++ mlpack/trunk/src/mlpack/tests/logistic_regression_test.cpp Wed Nov 13 13:02:30 2013
@@ -16,7 +16,7 @@
BOOST_AUTO_TEST_SUITE(LogisticRegressionTest);
/**
- * Test the LogisticFunction on a simple set of points.
+ * Test the LogisticRegressionFunction on a simple set of points.
*/
BOOST_AUTO_TEST_CASE(LogisticRegressionFunctionEvaluate)
{
@@ -38,4 +38,46 @@
BOOST_REQUIRE_CLOSE(lrf.Evaluate(arma::vec("200 -100 20")), 0.0, 1e-5);
}
+/**
+ * A more complicated test for the LogisticRegressionFunction.
+ */
+BOOST_AUTO_TEST_CASE(LogisticRegressionFunctionRandomEvaluate)
+{
+ const size_t points = 1000;
+ const size_t dimension = 10;
+ const size_t trials = 50;
+
+ // Create a random dataset.
+ arma::mat data;
+ data.randu(dimension, points);
+ // Create random responses.
+ arma::vec responses(points);
+ for (size_t i = 0; i < points; ++i)
+ responses[i] = math::RandInt(0, 2);
+
+ LogisticRegressionFunction lrf(data, responses, 0.0 /* no regularization */);
+
+ // Run a bunch of trials.
+ for (size_t i = 0; i < trials; ++i)
+ {
+ // Generate a random set of parameters.
+ arma::vec parameters;
+ parameters.randu(dimension);
+
+ // Hand-calculate the loss function.
+ double loglikelihood = 0.0;
+ for (size_t j = 0; j < points; ++j)
+ {
+ const double sigmoid = (1.0 / (1.0 +
+ exp(-arma::dot(data.col(j), parameters))));
+ if (responses[j] == 1.0)
+ loglikelihood += log(std::pow(sigmoid, responses[j]));
+ else
+ loglikelihood += log(std::pow(1.0 - sigmoid, 1.0 - responses[j]));
+ }
+
+ BOOST_REQUIRE_CLOSE(lrf.Evaluate(parameters), -loglikelihood, 1e-5);
+ }
+}
+
BOOST_AUTO_TEST_SUITE_END();
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