xgboost/tests/cpp/metric/test_rank_metric.cc
Jiaming Yuan bcc0277338
Re-implement ROC-AUC. (#6747)
* Re-implement ROC-AUC.

* Binary
* MultiClass
* LTR
* Add documents.

This PR resolves a few issues:
  - Define a value when the dataset is invalid, which can happen if there's an
  empty dataset, or when the dataset contains only positive or negative values.
  - Define ROC-AUC for multi-class classification.
  - Define weighted average value for distributed setting.
  - A correct implementation for learning to rank task.  Previous
  implementation is just binary classification with averaging across groups,
  which doesn't measure ordered learning to rank.
2021-03-20 16:52:40 +08:00

217 lines
8.8 KiB
C++

// Copyright by Contributors
#include <xgboost/metric.h>
#include "../helpers.h"
#if !defined(__CUDACC__)
TEST(Metric, AMS) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
EXPECT_ANY_THROW(xgboost::Metric::Create("ams", &tparam));
xgboost::Metric * metric = xgboost::Metric::Create("ams@0.5f", &tparam);
ASSERT_STREQ(metric->Name(), "ams@0.5");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.311f, 0.001f);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.29710f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ams@0", &tparam);
ASSERT_STREQ(metric->Name(), "ams@0");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.311f, 0.001f);
delete metric;
}
#endif
TEST(Metric, DeclareUnifiedTest(AUCPR)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric *metric = xgboost::Metric::Create("aucpr", &tparam);
ASSERT_STREQ(metric->Name(), "aucpr");
EXPECT_NEAR(GetMetricEval(metric, {0, 0, 1, 1}, {0, 0, 1, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric, {0.1f, 0.9f, 0.1f, 0.9f}, {0, 0, 1, 1}),
0.5f, 0.001f);
EXPECT_NEAR(
GetMetricEval(metric,
{0.4f, 0.2f, 0.9f, 0.1f, 0.2f, 0.4f, 0.1f, 0.1f, 0.2f, 0.1f},
{0, 0, 0, 0, 0, 1, 0, 0, 1, 1}),
0.2908445f, 0.001f);
EXPECT_NEAR(GetMetricEval(
metric, {0.87f, 0.31f, 0.40f, 0.42f, 0.25f, 0.66f, 0.95f,
0.09f, 0.10f, 0.97f, 0.76f, 0.69f, 0.15f, 0.20f,
0.30f, 0.14f, 0.07f, 0.58f, 0.61f, 0.08f},
{0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1}),
0.2769199f, 0.001f);
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 0}, {0, 0}));
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 0}, {1, 1}));
// AUCPR with instance weights
EXPECT_NEAR(GetMetricEval(
metric, {0.29f, 0.52f, 0.11f, 0.21f, 0.219f, 0.93f, 0.493f,
0.17f, 0.47f, 0.13f, 0.43f, 0.59f, 0.87f, 0.007f},
{0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0},
{1, 2, 7, 4, 5, 2.2f, 3.2f, 5, 6, 1, 2, 1.1f, 3.2f, 4.5f}), // weights
0.694435f, 0.001f);
// AUCPR with groups and no weights
EXPECT_NEAR(GetMetricEval(
metric, {0.87f, 0.31f, 0.40f, 0.42f, 0.25f, 0.66f, 0.95f,
0.09f, 0.10f, 0.97f, 0.76f, 0.69f, 0.15f, 0.20f,
0.30f, 0.14f, 0.07f, 0.58f, 0.61f, 0.08f},
{0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1},
{}, // weights
{0, 2, 5, 9, 14, 20}), // group info
0.556021f, 0.001f);
// AUCPR with groups and weights
EXPECT_NEAR(GetMetricEval(
metric, {0.29f, 0.52f, 0.11f, 0.21f, 0.219f, 0.93f, 0.493f,
0.17f, 0.47f, 0.13f, 0.43f, 0.59f, 0.87f, 0.007f}, // predictions
{0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 1, 0},
{1, 2, 7, 4, 5, 2.2f, 3.2f, 5, 6, 1, 2, 1.1f, 3.2f, 4.5f}, // weights
{0, 2, 5, 9, 14}), // group info
0.8150615f, 0.001f);
// Exception scenarios for grouped datasets
EXPECT_ANY_THROW(GetMetricEval(metric,
{0, 0.1f, 0.3f, 0.5f, 0.7f},
{1, 1, 0, 0, 0},
{},
{0, 2, 5}));
delete metric;
}
TEST(Metric, DeclareUnifiedTest(Precision)) {
// When the limit for precision is not given, it takes the limit at
// std::numeric_limits<unsigned>::max(); hence all values are very small
// NOTE(AbdealiJK): Maybe this should be fixed to be num_row by default.
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("pre", &tparam);
ASSERT_STREQ(metric->Name(), "pre");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0, 1e-7);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0, 1e-7);
delete metric;
metric = xgboost::Metric::Create("pre@2", &tparam);
ASSERT_STREQ(metric->Name(), "pre@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.5f, 1e-7);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.5f, 0.001f);
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
delete metric;
}
TEST(Metric, DeclareUnifiedTest(NDCG)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("ndcg", &tparam);
ASSERT_STREQ(metric->Name(), "ndcg");
EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@2", &tparam);
ASSERT_STREQ(metric->Name(), "ndcg@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.3868f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@-", &tparam);
ASSERT_STREQ(metric->Name(), "ndcg-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg-", &tparam);
ASSERT_STREQ(metric->Name(), "ndcg-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.6509f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("ndcg@2-", &tparam);
ASSERT_STREQ(metric->Name(), "ndcg@2-");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.3868f, 0.001f);
delete metric;
}
TEST(Metric, DeclareUnifiedTest(MAP)) {
auto tparam = xgboost::CreateEmptyGenericParam(GPUIDX);
xgboost::Metric * metric = xgboost::Metric::Create("map", &tparam);
ASSERT_STREQ(metric->Name(), "map");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.5f, 0.001f);
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
std::vector<xgboost::bst_float>{}), 1, 1e-10);
// Rank metric with group info
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.2f, 0.8f, 0.4f, 1.7f},
{2, 7, 1, 0, 5, 0}, // Labels
{}, // Weights
{0, 2, 5, 6}), // Group info
0.8611f, 0.001f);
delete metric;
metric = xgboost::Metric::Create("map@-", &tparam);
ASSERT_STREQ(metric->Name(), "map-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
delete metric;
metric = xgboost::Metric::Create("map-", &tparam);
ASSERT_STREQ(metric->Name(), "map-");
EXPECT_NEAR(GetMetricEval(metric,
xgboost::HostDeviceVector<xgboost::bst_float>{},
{}), 0, 1e-10);
delete metric;
metric = xgboost::Metric::Create("map@2", &tparam);
ASSERT_STREQ(metric->Name(), "map@2");
EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 1, 1e-10);
EXPECT_NEAR(GetMetricEval(metric,
{0.1f, 0.9f, 0.1f, 0.9f},
{ 0, 0, 1, 1}),
0.25f, 0.001f);
delete metric;
}