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Example 16 with LimeExplainer

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

the class OpenNLPLimeExplainerTest method testExplanationStabilityWithOptimization.

@Test
void testExplanationStabilityWithOptimization() throws ExecutionException, InterruptedException, TimeoutException, IOException {
    PredictionProvider model = getModel();
    List<PredictionInput> samples = getSamples(getTokenizer());
    List<PredictionOutput> predictionOutputs = model.predictAsync(samples.subList(0, 5)).get();
    List<Prediction> predictions = DataUtils.getPredictions(samples, predictionOutputs);
    long seed = 0;
    LimeConfigOptimizer limeConfigOptimizer = new LimeConfigOptimizer().withDeterministicExecution(true).withSampling(false).withStepCountLimit(30);
    Random random = new Random();
    LimeConfig limeConfig = new LimeConfig().withSamples(10).withPerturbationContext(new PerturbationContext(seed, random, 1));
    LimeConfig optimizedConfig = limeConfigOptimizer.optimize(limeConfig, predictions, model);
    Assertions.assertThat(optimizedConfig).isNotSameAs(limeConfig);
    LimeExplainer limeExplainer = new LimeExplainer(optimizedConfig);
    PredictionInput testPredictionInput = getTestInput(getTokenizer());
    List<PredictionOutput> testPredictionOutputs = model.predictAsync(List.of(testPredictionInput)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    Prediction instance = new SimplePrediction(testPredictionInput, testPredictionOutputs.get(0));
    assertDoesNotThrow(() -> ValidationUtils.validateLocalSaliencyStability(model, instance, limeExplainer, 1, 0.8, 0.8));
}
Also used : SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PerturbationContext(org.kie.kogito.explainability.model.PerturbationContext) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Prediction(org.kie.kogito.explainability.model.Prediction) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Random(java.util.Random) PredictionOutput(org.kie.kogito.explainability.model.PredictionOutput) LimeConfigOptimizer(org.kie.kogito.explainability.local.lime.optim.LimeConfigOptimizer) Test(org.junit.jupiter.api.Test) ParameterizedTest(org.junit.jupiter.params.ParameterizedTest)

Example 17 with LimeExplainer

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

the class PmmlCompoundScorecardLimeExplainerTest method testPMMLCompoundScorecard.

@Test
void testPMMLCompoundScorecard() throws Exception {
    Random random = new Random();
    LimeConfig limeConfig = new LimeConfig().withSamples(10).withPerturbationContext(new PerturbationContext(0L, random, 1));
    LimeExplainer limeExplainer = new LimeExplainer(limeConfig);
    PredictionInput input = getTestInput();
    PredictionProvider model = getModel();
    List<PredictionOutput> predictionOutputs = model.predictAsync(List.of(input)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    assertThat(predictionOutputs).isNotNull();
    assertThat(predictionOutputs).isNotEmpty();
    PredictionOutput output = predictionOutputs.get(0);
    assertThat(output).isNotNull();
    Prediction prediction = new SimplePrediction(input, output);
    Map<String, Saliency> saliencyMap = limeExplainer.explainAsync(prediction, model).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    for (Saliency saliency : saliencyMap.values()) {
        assertThat(saliency).isNotNull();
        double v = ExplainabilityMetrics.impactScore(model, prediction, saliency.getTopFeatures(2));
        assertThat(v).isEqualTo(1d);
    }
    assertDoesNotThrow(() -> ValidationUtils.validateLocalSaliencyStability(model, prediction, limeExplainer, 1, 0.5, 0.5));
    List<PredictionInput> inputs = getSamples();
    DataDistribution distribution = new PredictionInputsDataDistribution(inputs);
    String decision = "score";
    int k = 1;
    int chunkSize = 2;
    double f1 = ExplainabilityMetrics.getLocalSaliencyF1(decision, model, limeExplainer, distribution, k, chunkSize);
    AssertionsForClassTypes.assertThat(f1).isBetween(0d, 1d);
}
Also used : SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PerturbationContext(org.kie.kogito.explainability.model.PerturbationContext) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Prediction(org.kie.kogito.explainability.model.Prediction) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) Saliency(org.kie.kogito.explainability.model.Saliency) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Random(java.util.Random) PredictionInputsDataDistribution(org.kie.kogito.explainability.model.PredictionInputsDataDistribution) DataDistribution(org.kie.kogito.explainability.model.DataDistribution) PredictionOutput(org.kie.kogito.explainability.model.PredictionOutput) PredictionInputsDataDistribution(org.kie.kogito.explainability.model.PredictionInputsDataDistribution) Test(org.junit.jupiter.api.Test)

Example 18 with LimeExplainer

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

the class PmmlCompoundScorecardLimeExplainerTest method testExplanationWeightedStabilityWithOptimization.

@Test
void testExplanationWeightedStabilityWithOptimization() throws ExecutionException, InterruptedException, TimeoutException {
    PredictionProvider model = getModel();
    List<PredictionInput> samples = getSamples();
    List<PredictionOutput> predictionOutputs = model.predictAsync(samples.subList(0, 5)).get();
    List<Prediction> predictions = DataUtils.getPredictions(samples, predictionOutputs);
    long seed = 0;
    LimeConfigOptimizer limeConfigOptimizer = new LimeConfigOptimizer().withDeterministicExecution(true).withWeightedStability(0.4, 0.6);
    Random random = new Random();
    PerturbationContext perturbationContext = new PerturbationContext(seed, random, 1);
    LimeConfig initialConfig = new LimeConfig().withSamples(10).withPerturbationContext(perturbationContext);
    LimeConfig optimizedConfig = limeConfigOptimizer.optimize(initialConfig, predictions, model);
    assertThat(optimizedConfig).isNotSameAs(initialConfig);
    LimeExplainer limeExplainer = new LimeExplainer(optimizedConfig);
    PredictionInput testPredictionInput = getTestInput();
    List<PredictionOutput> testPredictionOutputs = model.predictAsync(List.of(testPredictionInput)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    Prediction instance = new SimplePrediction(testPredictionInput, testPredictionOutputs.get(0));
    assertDoesNotThrow(() -> ValidationUtils.validateLocalSaliencyStability(model, instance, limeExplainer, 1, 0.5, 0.7));
}
Also used : SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PerturbationContext(org.kie.kogito.explainability.model.PerturbationContext) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Prediction(org.kie.kogito.explainability.model.Prediction) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Random(java.util.Random) PredictionOutput(org.kie.kogito.explainability.model.PredictionOutput) LimeConfigOptimizer(org.kie.kogito.explainability.local.lime.optim.LimeConfigOptimizer) Test(org.junit.jupiter.api.Test)

Example 19 with LimeExplainer

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

the class PmmlRegressionCategoricalLimeExplainerTest method testExplanationStabilityWithOptimization.

@Disabled("See KOGITO-6154")
@Test
void testExplanationStabilityWithOptimization() throws ExecutionException, InterruptedException, TimeoutException {
    PredictionProvider model = getModel();
    List<PredictionInput> samples = getSamples();
    List<PredictionOutput> predictionOutputs = model.predictAsync(samples.subList(0, 5)).get();
    List<Prediction> predictions = DataUtils.getPredictions(samples, predictionOutputs);
    long seed = 0;
    LimeConfigOptimizer limeConfigOptimizer = new LimeConfigOptimizer().withDeterministicExecution(true);
    Random random = new Random();
    PerturbationContext perturbationContext = new PerturbationContext(seed, random, 1);
    LimeConfig initialConfig = new LimeConfig().withSamples(10).withPerturbationContext(perturbationContext);
    LimeConfig optimizedConfig = limeConfigOptimizer.optimize(initialConfig, predictions, model);
    assertThat(optimizedConfig).isNotSameAs(initialConfig);
    LimeExplainer limeExplainer = new LimeExplainer(optimizedConfig);
    PredictionInput testPredictionInput = getTestInput();
    List<PredictionOutput> testPredictionOutputs = model.predictAsync(List.of(testPredictionInput)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    Prediction instance = new SimplePrediction(testPredictionInput, testPredictionOutputs.get(0));
    assertDoesNotThrow(() -> ValidationUtils.validateLocalSaliencyStability(model, instance, limeExplainer, 1, 0.6, 0.6));
}
Also used : SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PerturbationContext(org.kie.kogito.explainability.model.PerturbationContext) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Prediction(org.kie.kogito.explainability.model.Prediction) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Random(java.util.Random) PredictionOutput(org.kie.kogito.explainability.model.PredictionOutput) LimeConfigOptimizer(org.kie.kogito.explainability.local.lime.optim.LimeConfigOptimizer) Test(org.junit.jupiter.api.Test) Disabled(org.junit.jupiter.api.Disabled)

Example 20 with LimeExplainer

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

the class ExplainabilityMetricsTest method testFidelityWithTextClassifier.

@Test
void testFidelityWithTextClassifier() throws ExecutionException, InterruptedException, TimeoutException {
    List<Pair<Saliency, Prediction>> pairs = new LinkedList<>();
    LimeConfig limeConfig = new LimeConfig().withSamples(10);
    LimeExplainer limeExplainer = new LimeExplainer(limeConfig);
    PredictionProvider model = TestUtils.getDummyTextClassifier();
    List<Feature> features = new LinkedList<>();
    features.add(FeatureFactory.newFulltextFeature("f-0", "brown fox", s -> Arrays.asList(s.split(" "))));
    features.add(FeatureFactory.newTextFeature("f-1", "money"));
    PredictionInput input = new PredictionInput(features);
    Prediction prediction = new SimplePrediction(input, model.predictAsync(List.of(input)).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit()).get(0));
    Map<String, Saliency> saliencyMap = limeExplainer.explainAsync(prediction, model).get(Config.INSTANCE.getAsyncTimeout(), Config.INSTANCE.getAsyncTimeUnit());
    for (Saliency saliency : saliencyMap.values()) {
        pairs.add(Pair.of(saliency, prediction));
    }
    Assertions.assertDoesNotThrow(() -> {
        ExplainabilityMetrics.classificationFidelity(pairs);
    });
}
Also used : FeatureFactory(org.kie.kogito.explainability.model.FeatureFactory) Arrays(java.util.Arrays) Feature(org.kie.kogito.explainability.model.Feature) Prediction(org.kie.kogito.explainability.model.Prediction) Assertions.assertThat(org.assertj.core.api.Assertions.assertThat) TimeoutException(java.util.concurrent.TimeoutException) Saliency(org.kie.kogito.explainability.model.Saliency) Pair(org.apache.commons.lang3.tuple.Pair) Assertions.assertFalse(org.junit.jupiter.api.Assertions.assertFalse) Map(java.util.Map) CompletableFuture.supplyAsync(java.util.concurrent.CompletableFuture.supplyAsync) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Assertions.assertEquals(org.junit.jupiter.api.Assertions.assertEquals) LinkedList(java.util.LinkedList) PredictionOutput(org.kie.kogito.explainability.model.PredictionOutput) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) Awaitility.await(org.awaitility.Awaitility.await) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Collections.emptyList(java.util.Collections.emptyList) FeatureImportance(org.kie.kogito.explainability.model.FeatureImportance) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) ExecutionException(java.util.concurrent.ExecutionException) TimeUnit(java.util.concurrent.TimeUnit) Test(org.junit.jupiter.api.Test) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) List(java.util.List) TestUtils(org.kie.kogito.explainability.TestUtils) Assertions(org.junit.jupiter.api.Assertions) Config(org.kie.kogito.explainability.Config) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) PredictionInput(org.kie.kogito.explainability.model.PredictionInput) LimeExplainer(org.kie.kogito.explainability.local.lime.LimeExplainer) Prediction(org.kie.kogito.explainability.model.Prediction) SimplePrediction(org.kie.kogito.explainability.model.SimplePrediction) Saliency(org.kie.kogito.explainability.model.Saliency) PredictionProvider(org.kie.kogito.explainability.model.PredictionProvider) Feature(org.kie.kogito.explainability.model.Feature) LinkedList(java.util.LinkedList) LimeConfig(org.kie.kogito.explainability.local.lime.LimeConfig) Pair(org.apache.commons.lang3.tuple.Pair) Test(org.junit.jupiter.api.Test)

Aggregations

LimeExplainer (org.kie.kogito.explainability.local.lime.LimeExplainer)42 Prediction (org.kie.kogito.explainability.model.Prediction)38 Test (org.junit.jupiter.api.Test)37 LimeConfig (org.kie.kogito.explainability.local.lime.LimeConfig)36 PredictionProvider (org.kie.kogito.explainability.model.PredictionProvider)36 SimplePrediction (org.kie.kogito.explainability.model.SimplePrediction)35 PredictionInput (org.kie.kogito.explainability.model.PredictionInput)34 Random (java.util.Random)33 PerturbationContext (org.kie.kogito.explainability.model.PerturbationContext)33 PredictionOutput (org.kie.kogito.explainability.model.PredictionOutput)33 LimeConfigOptimizer (org.kie.kogito.explainability.local.lime.optim.LimeConfigOptimizer)19 Saliency (org.kie.kogito.explainability.model.Saliency)16 PredictionInputsDataDistribution (org.kie.kogito.explainability.model.PredictionInputsDataDistribution)13 DataDistribution (org.kie.kogito.explainability.model.DataDistribution)12 ArrayList (java.util.ArrayList)9 Feature (org.kie.kogito.explainability.model.Feature)7 ExecutionException (java.util.concurrent.ExecutionException)5 TimeoutException (java.util.concurrent.TimeoutException)5 FeatureImportance (org.kie.kogito.explainability.model.FeatureImportance)5 InputStreamReader (java.io.InputStreamReader)4