Examples with LimeExplainer org.kie.kogito.explainability.local.lime.LimeExplainer used on opensource projects

Example 26 with LimeExplainer

use of org.kie.kogito.explainability.local.lime.LimeExplainer in project kogito-apps by kiegroup.

the class DefaultLimeOptimizationServiceTest method testNullConfig.

@Test
void testNullConfig() {
    LimeConfigOptimizer optimizer = new LimeConfigOptimizer();
    int max = 1;
    LimeOptimizationService service = new DefaultLimeOptimizationService(optimizer, max);
    assertThat(service.getBestConfigFor(new LimeExplainer())).isNull();
}

Example 27 with LimeExplainer

use of org.kie.kogito.explainability.local.lime.LimeExplainer in project kogito-apps by kiegroup.

the class LimeStabilityScoreCalculator method getStabilityScore.

private BigDecimal getStabilityScore(PredictionProvider model, LimeConfig config, List<Prediction> predictions) {
    double succeededEvaluations = 0;
    int topK = 2;
    BigDecimal stabilityScore = BigDecimal.ZERO;
    LimeExplainer limeExplainer = new LimeExplainer(config);
    for (Prediction prediction : predictions) {
        try {
            LocalSaliencyStability stability = ExplainabilityMetrics.getLocalSaliencyStability(model, prediction, limeExplainer, topK, NUM_RUNS);
            for (String decision : stability.getDecisions()) {
                BigDecimal decisionMarginalScore = getDecisionMarginalScore(stability, decision, topK);
                stabilityScore = stabilityScore.add(decisionMarginalScore);
                succeededEvaluations++;
            }
        } catch (ExecutionException e) {
            LOGGER.error("Saliency stability calculation returned an error {}", e.getMessage());
        } catch (InterruptedException e) {
            LOGGER.error("Interrupted while waiting for saliency stability calculation {}", e.getMessage());
            Thread.currentThread().interrupt();
        } catch (TimeoutException e) {
            LOGGER.error("Timed out while waiting for saliency stability calculation", e);
        }
    }
    if (succeededEvaluations > 0) {
        stabilityScore = stabilityScore.divide(BigDecimal.valueOf(succeededEvaluations), RoundingMode.CEILING);
    }
    return stabilityScore;
}

Example 28 with LimeExplainer

use of org.kie.kogito.explainability.local.lime.LimeExplainer in project kogito-apps by kiegroup.

the class LimeExplainerProducerTest method produce.

@Test
void produce() {
    LimeExplainerProducer producer = new LimeExplainerProducer(1, 2, 10);
    LimeExplainer limeExplainer = producer.produce();
    assertNotNull(limeExplainer);
    assertEquals(1, limeExplainer.getLimeConfig().getNoOfSamples());
    assertEquals(2, limeExplainer.getLimeConfig().getPerturbationContext().getNoOfPerturbations());
    assertEquals(LimeConfig.DEFAULT_NO_OF_RETRIES, limeExplainer.getLimeConfig().getNoOfRetries());
}

Example 29 with LimeExplainer

use of org.kie.kogito.explainability.local.lime.LimeExplainer in project kogito-apps by kiegroup.

the class LocalExplainerServiceHandlerRegistryTest method setup.

@BeforeEach
@SuppressWarnings("unchecked")
public void setup() {
    LimeExplainer limeExplainer = mock(LimeExplainer.class);
    CounterfactualExplainer counterfactualExplainer = mock(CounterfactualExplainer.class);
    PredictionProviderFactory predictionProviderFactory = mock(PredictionProviderFactory.class);
    limeExplainerServiceHandler = spy(new LimeExplainerServiceHandler(limeExplainer, predictionProviderFactory));
    counterfactualExplainerServiceHandler = spy(new CounterfactualExplainerServiceHandler(counterfactualExplainer, predictionProviderFactory, MAX_RUNNING_TIME_SECONDS));
    predictionProvider = mock(PredictionProvider.class);
    callback = mock(Consumer.class);
    when(predictionProviderFactory.createPredictionProvider(any(), any(), any())).thenReturn(predictionProvider);
    Instance<LocalExplainerServiceHandler<?, ?>> explanationHandlers = mock(Instance.class);
    when(explanationHandlers.stream()).thenReturn(Stream.of(limeExplainerServiceHandler, counterfactualExplainerServiceHandler));
    registry = new LocalExplainerServiceHandlerRegistry(explanationHandlers);
}

Example 30 with LimeExplainer

use of org.kie.kogito.explainability.local.lime.LimeExplainer in project kogito-apps by kiegroup.

the class TrafficViolationDmnLimeExplainerTest method testTrafficViolationDMNExplanation.

@Test
void testTrafficViolationDMNExplanation() throws ExecutionException, InterruptedException, TimeoutException {
    PredictionProvider model = getModel();
    PredictionInput predictionInput = getTestInput();
    List<PredictionOutput> predictionOutputs = model.predictAsync(List.of(predictionInput)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    Prediction prediction = new SimplePrediction(predictionInput, predictionOutputs.get(0));
    Random random = new Random();
    PerturbationContext perturbationContext = new PerturbationContext(0L, random, 1);
    LimeConfig limeConfig = new LimeConfig().withSamples(10).withPerturbationContext(perturbationContext);
    LimeExplainer limeExplainer = new LimeExplainer(limeConfig);
    Map<String, Saliency> saliencyMap = limeExplainer.explainAsync(prediction, model).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    for (Saliency saliency : saliencyMap.values()) {
        assertNotNull(saliency);
        List<String> strings = saliency.getTopFeatures(3).stream().map(f -> f.getFeature().getName()).collect(Collectors.toList());
        assertTrue(strings.contains("Actual Speed") || strings.contains("Speed Limit"));
    }
    assertDoesNotThrow(() -> ValidationUtils.validateLocalSaliencyStability(model, prediction, limeExplainer, 1, 0.3, 0.3));
    String decision = "Fine";
    List<PredictionInput> inputs = new ArrayList<>();
    for (int n = 0; n < 10; n++) {
        inputs.add(new PredictionInput(DataUtils.perturbFeatures(predictionInput.getFeatures(), perturbationContext)));
    }
    DataDistribution distribution = new PredictionInputsDataDistribution(inputs);
    int k = 2;
    int chunkSize = 5;
    double f1 = ExplainabilityMetrics.getLocalSaliencyF1(decision, model, limeExplainer, distribution, k, chunkSize);
    AssertionsForClassTypes.assertThat(f1).isBetween(0.5d, 1d);
}