Fix mistakes in feature selection in SPnDE

Complete the first A2DE test
Update version number

.vscode/launch.json

@@ -16,7 +16,7 @@
             "name": "test",
             "program": "${workspaceFolder}/build_debug/tests/TestBayesNet",
             "args": [
-                "\"Bisection Best\""
+                "[A2DE]"
             ],
             "cwd": "${workspaceFolder}/build_debug/tests"
         },

CHANGELOG.md

@@ -9,9 +9,11 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Added
 
-- Add the Library logo generated with <https://openart.ai> to README.md
-- Add link to the coverage report in the README.md coverage label.
-- Add the *convergence_best* hyperparameter to the BoostAODE class, to control the way the prior accuracy is computed if convergence is set. Default value is *false*.
+- Library logo generated with <https://openart.ai> to README.md
+- Link to the coverage report in the README.md coverage label.
+- *convergence_best* hyperparameter to the BoostAODE class, to control the way the prior accuracy is computed if convergence is set. Default value is *false*.
+- SPnDE model.
+- A2DE model.
 
 ### Internal
 
@@ -19,6 +21,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Refactor catch2 library location to test/lib
 - Refactor loadDataset function in tests.
 - Remove conditionalEdgeWeights method in BayesMetrics.
+- A2DE & SPnDE tests.
 
 ## [1.0.5] 2024-04-20
 

CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.20)
 
 project(BayesNet
-  VERSION 1.0.5
+  VERSION 1.0.5.1
   DESCRIPTION "Bayesian Network and basic classifiers Library."
   HOMEPAGE_URL "https://github.com/rmontanana/bayesnet"
   LANGUAGES CXX

bayesnet/classifiers/SPnDE.cc

@@ -16,7 +16,7 @@ namespace bayesnet {
         addNodes();
         std::vector<int> attributes;
         for (int i = 0; i < static_cast<int>(features.size()); ++i) {
-            if (std::find(parents.begin(), parents.end(), i) != parents.end()) {
+            if (std::find(parents.begin(), parents.end(), i) == parents.end()) {
                 attributes.push_back(i);
             }
         }
@@ -25,6 +25,7 @@ namespace bayesnet {
         for (const auto& attribute : attributes) {
             model.addEdge(className, features[attribute]);
             for (const auto& root : parents) {
+
                 model.addEdge(features[root], features[attribute]);
             }
         }

bayesnet/ensembles/A2DE.cc

@@ -27,10 +27,11 @@ namespace bayesnet {
         significanceModels.clear();
         for (int i = 0; i < features.size() - 1; ++i) {
             for (int j = i + 1; j < features.size(); ++j) {
-                models.push_back(std::make_unique<SPnDE>(std::vector<int>({ i, j })));
+                auto model = std::make_unique<SPnDE>(std::vector<int>({ i, j }));
+                models.push_back(std::move(model));
             }
         }
-        n_models = models.size();
+        n_models = static_cast<unsigned>(models.size());
         significanceModels = std::vector<double>(n_models, 1.0);
     }
     std::vector<std::string> A2DE::graph(const std::string& title) const

tests/CMakeLists.txt

@@ -9,7 +9,7 @@ if(ENABLE_TESTING)
     )
     file(GLOB_RECURSE BayesNet_SOURCES "${BayesNet_SOURCE_DIR}/bayesnet/*.cc")
     add_executable(TestBayesNet TestBayesNetwork.cc TestBayesNode.cc TestBayesClassifier.cc 
-        TestBayesModels.cc TestBayesMetrics.cc TestFeatureSelection.cc TestBoostAODE.cc
+        TestBayesModels.cc TestBayesMetrics.cc TestFeatureSelection.cc TestBoostAODE.cc TestA2DE.cc
         TestUtils.cc TestBayesEnsemble.cc ${BayesNet_SOURCES})
     target_link_libraries(TestBayesNet PUBLIC "${TORCH_LIBRARIES}" ArffFiles mdlp PRIVATE Catch2::Catch2WithMain)
     add_test(NAME BayesNetworkTest COMMAND TestBayesNet)

tests/TestA2DE.cc

@@ -17,10 +17,8 @@ TEST_CASE("Fit and Score", "[A2DE]")
     auto raw = RawDatasets("glass", true);
     auto clf = bayesnet::A2DE();
     clf.fit(raw.Xv, raw.yv, raw.features, raw.className, raw.states);
-    std::cout << "Score A2DE: " << clf.score(raw.Xv, raw.yv) << std::endl;
-    // REQUIRE(clf.getNumberOfNodes() == 90);
-    // REQUIRE(clf.getNumberOfEdges() == 153);
-    // REQUIRE(clf.getNotes().size() == 2);
-    // REQUIRE(clf.getNotes()[0] == "Used features in initialization: 6 of 9 with CFS");
-    // REQUIRE(clf.getNotes()[1] == "Number of models: 9");
+    REQUIRE(clf.score(raw.Xv, raw.yv) == Catch::Approx(0.831776).epsilon(raw.epsilon));
+    REQUIRE(clf.getNumberOfNodes() == 360);
+    REQUIRE(clf.getNumberOfEdges() == 756);
+    REQUIRE(clf.getNotes().size() == 0);
 }