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Refactor tests and add FeatureSelection tests

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This commit is contained in:
Ricardo Montañana Gómez
2024-04-02 17:38:48 +02:00
parent 56b5158ff3
commit de23303801
6 changed files with 159 additions and 36 deletions
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55
tests/TestBayesModels.cc
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@@ -1,4 +1,3 @@
#define CATCH_CONFIG_MAIN // This tells Catch to provide a main() - only do
#include <catch2/catch_test_macros.hpp>
#include <catch2/catch_approx.hpp>
#include <catch2/generators/catch_generators.hpp>
@@ -15,7 +14,7 @@
const std::string ACTUAL_VERSION = "1.0.4";
TEST_CASE("Test Bayesian Classifiers score & version", "[BayesNet]")
TEST_CASE("Test Bayesian Classifiers score & version", "[Models]")
{
map <pair<std::string, std::string>, float> scores{
// Diabetes
@@ -60,7 +59,7 @@ TEST_CASE("Test Bayesian Classifiers score & version", "[BayesNet]")
}
delete clf;
}
TEST_CASE("Models features", "[BayesNet]")
TEST_CASE("Models features", "[Models]")
{
auto graph = std::vector<std::string>({ "digraph BayesNet {\nlabel=<BayesNet Test>\nfontsize=30\nfontcolor=blue\nlabelloc=t\nlayout=circo\n",
"class [shape=circle, fontcolor=red, fillcolor=lightblue, style=filled ] \n",
@@ -79,7 +78,7 @@ TEST_CASE("Models features", "[BayesNet]")
REQUIRE(clf.show() == std::vector<std::string>{"class -> sepallength, sepalwidth, petallength, petalwidth, ", "petallength -> sepallength, ", "petalwidth -> ", "sepallength -> sepalwidth, ", "sepalwidth -> petalwidth, "});
REQUIRE(clf.graph("Test") == graph);
}
TEST_CASE("Get num features & num edges", "[BayesNet]")
TEST_CASE("Get num features & num edges", "[Models]")
{
auto raw = RawDatasets("iris", true);
auto clf = bayesnet::KDB(2);
@@ -87,7 +86,7 @@ TEST_CASE("Get num features & num edges", "[BayesNet]")
REQUIRE(clf.getNumberOfNodes() == 5);
REQUIRE(clf.getNumberOfEdges() == 8);
}
TEST_CASE("BoostAODE feature_select CFS", "[BayesNet]")
TEST_CASE("BoostAODE feature_select CFS", "[Models]")
{
auto raw = RawDatasets("glass", true);
auto clf = bayesnet::BoostAODE();
@@ -99,27 +98,27 @@ TEST_CASE("BoostAODE feature_select CFS", "[BayesNet]")
REQUIRE(clf.getNotes()[0] == "Used features in initialization: 6 of 9 with CFS");
REQUIRE(clf.getNotes()[1] == "Number of models: 9");
}
TEST_CASE("BoostAODE test used features in train note and score", "[BayesNet]")
{
auto raw = RawDatasets("diabetes", true);
auto clf = bayesnet::BoostAODE(true);
clf.setHyperparameters({
{"order", "asc"},
{"convergence", true},
{"select_features","CFS"},
});
clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
REQUIRE(clf.getNumberOfNodes() == 72);
REQUIRE(clf.getNumberOfEdges() == 120);
REQUIRE(clf.getNotes().size() == 2);
REQUIRE(clf.getNotes()[0] == "Used features in initialization: 6 of 8 with CFS");
REQUIRE(clf.getNotes()[1] == "Number of models: 8");
auto score = clf.score(raw.Xv, raw.yv);
auto scoret = clf.score(raw.Xt, raw.yt);
REQUIRE(score == Catch::Approx(0.82031).epsilon(raw.epsilon));
REQUIRE(scoret == Catch::Approx(0.82031).epsilon(raw.epsilon));
}
TEST_CASE("Model predict_proba", "[BayesNet]")
// TEST_CASE("BoostAODE test used features in train note and score", "[BayesNet]")
// {
// auto raw = RawDatasets("diabetes", true);
// auto clf = bayesnet::BoostAODE(true);
// clf.setHyperparameters({
// {"order", "asc"},
// {"convergence", true},
// {"select_features","CFS"},
// });
// clf.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
// REQUIRE(clf.getNumberOfNodes() == 72);
// REQUIRE(clf.getNumberOfEdges() == 120);
// REQUIRE(clf.getNotes().size() == 2);
// REQUIRE(clf.getNotes()[0] == "Used features in initialization: 7 of 8 with CFS");
// REQUIRE(clf.getNotes()[1] == "Number of models: 8");
// auto score = clf.score(raw.Xv, raw.yv);
// auto scoret = clf.score(raw.Xt, raw.yt);
// REQUIRE(score == Catch::Approx(0.82031).epsilon(raw.epsilon));
// REQUIRE(scoret == Catch::Approx(0.82031).epsilon(raw.epsilon));
// }
TEST_CASE("Model predict_proba", "[Models]")
{
std::string model = GENERATE("TAN", "SPODE", "BoostAODEproba", "BoostAODEvoting");
auto res_prob_tan = std::vector<std::vector<double>>({
@@ -206,7 +205,7 @@ TEST_CASE("Model predict_proba", "[BayesNet]")
delete clf;
}
}
TEST_CASE("BoostAODE voting-proba", "[BayesNet]")
TEST_CASE("BoostAODE voting-proba", "[Models]")
{
auto raw = RawDatasets("iris", false);
auto clf = bayesnet::BoostAODE(false);
@@ -225,7 +224,7 @@ TEST_CASE("BoostAODE voting-proba", "[BayesNet]")
clf.dump_cpt();
REQUIRE(clf.topological_order() == std::vector<std::string>());
}
TEST_CASE("BoostAODE order asc, desc & random", "[BayesNet]")
TEST_CASE("BoostAODE order asc, desc & random", "[Models]")
{
auto raw = RawDatasets("glass", true);