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fimdlp/fimdlp/testcpp/Metrics_unittest.cc

31 lines
1.2 KiB
C++

#include "gtest/gtest.h"
#include "../Metrics.h"
namespace mdlp {
precision_t precision = 0.000001;
TEST(MetricTest, NumClasses)
{
labels y = { 1, 1, 1, 1, 1, 1, 1, 1, 2, 1 };
indices_t indices = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
EXPECT_EQ(1, Metrics::numClasses(y, indices, 4, 8));
EXPECT_EQ(2, Metrics::numClasses(y, indices, 0, 10));
EXPECT_EQ(2, Metrics::numClasses(y, indices, 8, 10));
}
TEST(MetricTest, Entropy)
{
labels y = { 1, 1, 1, 1, 1, 2, 2, 2, 2, 2 };
indices_t indices = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
EXPECT_EQ(1, Metrics::entropy(y, indices, 0, 10, 2));
EXPECT_EQ(0, Metrics::entropy(y, indices, 0, 5, 1));
labels yz = { 1, 1, 1, 1, 1, 1, 1, 1, 2, 1 };
ASSERT_NEAR(0.468996, Metrics::entropy(yz, indices, 0, 10, 2), precision);
}
TEST(MetricTest, InformationGain)
{
labels y = { 1, 1, 1, 1, 1, 2, 2, 2, 2, 2 };
indices_t indices = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
labels yz = { 1, 1, 1, 1, 1, 1, 1, 1, 2, 1 };
ASSERT_NEAR(1, Metrics::informationGain(y, indices, 0, 10, 5, 2), precision);
ASSERT_NEAR(0.108032, Metrics::informationGain(yz, indices, 0, 10, 5, 2), precision);
}
}