Make some boostAODE tests
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@@ -3,6 +3,8 @@
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#include <string>
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#include "TestUtils.h"
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#include "bayesnet/classifiers/TAN.h"
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#include "bayesnet/classifiers/KDB.h"
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#include "bayesnet/classifiers/KDBLd.h"
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TEST_CASE("Test Cannot build dataset with wrong data vector", "[Classifier]")
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@@ -83,4 +85,20 @@ TEST_CASE("Not fitted model", "[Classifier]")
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REQUIRE_THROWS_WITH(model.predict_proba(raw.Xv), message);
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REQUIRE_THROWS_AS(model.score(raw.Xv, raw.yv), std::logic_error);
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REQUIRE_THROWS_WITH(model.score(raw.Xv, raw.yv), message);
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}
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TEST_CASE("KDB Graph", "[Classifier]")
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{
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auto model = bayesnet::KDB(2);
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auto raw = RawDatasets("iris", true);
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model.fit(raw.Xv, raw.yv, raw.featuresv, raw.classNamev, raw.statesv);
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auto graph = model.graph();
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REQUIRE(graph.size() == 15);
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}
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TEST_CASE("KDBLd Graph", "[Classifier]")
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{
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auto model = bayesnet::KDBLd(2);
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auto raw = RawDatasets("iris", false);
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model.fit(raw.Xt, raw.yt, raw.featurest, raw.classNamet, raw.statest);
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auto graph = model.graph();
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REQUIRE(graph.size() == 15);
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}
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