use of org.kie.kogito.decision.DecisionModel in project kogito-apps by kiegroup.
the class TrafficViolationDmnLimeExplainerTest method getModel.
private PredictionProvider getModel() {
DMNRuntime dmnRuntime = DMNKogito.createGenericDMNRuntime(new InputStreamReader(getClass().getResourceAsStream("/dmn/TrafficViolation.dmn")));
assertEquals(1, dmnRuntime.getModels().size());
final String TRAFFIC_VIOLATION_NS = "https://github.com/kiegroup/drools/kie-dmn/_A4BCA8B8-CF08-433F-93B2-A2598F19ECFF";
final String TRAFFIC_VIOLATION_NAME = "Traffic Violation";
DecisionModel decisionModel = new DmnDecisionModel(dmnRuntime, TRAFFIC_VIOLATION_NS, TRAFFIC_VIOLATION_NAME);
return new DecisionModelWrapper(decisionModel);
}
use of org.kie.kogito.decision.DecisionModel in project kogito-apps by kiegroup.
the class TrafficViolationDmnPDPExplainerTest method testTrafficViolationDMNExplanation.
@Test
void testTrafficViolationDMNExplanation() throws ExecutionException, InterruptedException, TimeoutException {
DMNRuntime dmnRuntime = DMNKogito.createGenericDMNRuntime(new InputStreamReader(getClass().getResourceAsStream("/dmn/TrafficViolation.dmn")));
assertEquals(1, dmnRuntime.getModels().size());
final String TRAFFIC_VIOLATION_NS = "https://github.com/kiegroup/drools/kie-dmn/_A4BCA8B8-CF08-433F-93B2-A2598F19ECFF";
final String TRAFFIC_VIOLATION_NAME = "Traffic Violation";
DecisionModel decisionModel = new DmnDecisionModel(dmnRuntime, TRAFFIC_VIOLATION_NS, TRAFFIC_VIOLATION_NAME);
PredictionProvider model = new DecisionModelWrapper(decisionModel);
List<PredictionInput> inputs = DmnTestUtils.randomTrafficViolationInputs();
List<PredictionOutput> predictionOutputs = model.predictAsync(inputs).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
List<Prediction> predictions = new ArrayList<>();
for (int i = 0; i < predictionOutputs.size(); i++) {
predictions.add(new SimplePrediction(inputs.get(i), predictionOutputs.get(i)));
}
PartialDependencePlotExplainer partialDependencePlotExplainer = new PartialDependencePlotExplainer();
List<PartialDependenceGraph> pdps = partialDependencePlotExplainer.explainFromPredictions(model, predictions);
AssertionsForClassTypes.assertThat(pdps).isNotNull();
Assertions.assertThat(pdps).hasSize(8);
}
use of org.kie.kogito.decision.DecisionModel in project kogito-apps by kiegroup.
the class LoanEligibilityDmnCounterfactualExplainerTest method getModel.
private PredictionProvider getModel() {
DMNRuntime dmnRuntime = DMNKogito.createGenericDMNRuntime(new InputStreamReader(Objects.requireNonNull(getClass().getResourceAsStream("/dmn/LoanEligibility.dmn"))));
assertEquals(1, dmnRuntime.getModels().size());
final String FRAUD_NS = "https://github.com/kiegroup/kogito-examples/dmn-quarkus-listener-example";
final String FRAUD_NAME = "LoanEligibility";
DecisionModel decisionModel = new DmnDecisionModel(dmnRuntime, FRAUD_NS, FRAUD_NAME);
return new DecisionModelWrapper(decisionModel, List.of("Judgement"));
}
use of org.kie.kogito.decision.DecisionModel in project kogito-apps by kiegroup.
the class PrequalificationDmnCounterfactualExplainerTest method getModel.
private PredictionProvider getModel() {
DMNRuntime dmnRuntime = DMNKogito.createGenericDMNRuntime(new InputStreamReader(getClass().getResourceAsStream("/dmn/Prequalification-1.dmn")));
assertEquals(1, dmnRuntime.getModels().size());
final String NS = "http://www.trisotech.com/definitions/_f31e1f8e-d4ce-4a3a-ac3b-747efa6b3401";
final String NAME = "Prequalification";
DecisionModel decisionModel = new DmnDecisionModel(dmnRuntime, NS, NAME);
return new DecisionModelWrapper(decisionModel, List.of("LTV", "LLPA", "DTI", "Loan Payment"));
}
use of org.kie.kogito.decision.DecisionModel in project kogito-apps by kiegroup.
the class PrequalificationDmnPDPExplainerTest method testPrequalificationDMNExplanation.
@Test
void testPrequalificationDMNExplanation() throws ExecutionException, InterruptedException, TimeoutException {
DMNRuntime dmnRuntime = DMNKogito.createGenericDMNRuntime(new InputStreamReader(getClass().getResourceAsStream("/dmn/Prequalification-1.dmn")));
assertEquals(1, dmnRuntime.getModels().size());
final String NS = "http://www.trisotech.com/definitions/_f31e1f8e-d4ce-4a3a-ac3b-747efa6b3401";
final String NAME = "Prequalification";
DecisionModel decisionModel = new DmnDecisionModel(dmnRuntime, NS, NAME);
PredictionProvider model = new DecisionModelWrapper(decisionModel);
List<PredictionInput> inputs = DmnTestUtils.randomPrequalificationInputs();
List<PredictionOutput> predictionOutputs = model.predictAsync(inputs).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
List<Prediction> predictions = new ArrayList<>();
for (int i = 0; i < predictionOutputs.size(); i++) {
predictions.add(new SimplePrediction(inputs.get(i), predictionOutputs.get(i)));
}
PartialDependencePlotExplainer partialDependencePlotExplainer = new PartialDependencePlotExplainer();
List<PartialDependenceGraph> pdps = partialDependencePlotExplainer.explainFromPredictions(model, predictions);
AssertionsForClassTypes.assertThat(pdps).isNotNull();
Assertions.assertThat(pdps).hasSize(25);
}
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