Examples with DynamicAttributionVisitor com.amazon.randomcutforest.anomalydetection.DynamicAttributionVisitor used on opensource projects

Example 1 with DynamicAttributionVisitor

use of com.amazon.randomcutforest.anomalydetection.DynamicAttributionVisitor in project random-cut-forest-by-aws by aws.

the class RandomCutForest method getApproximateDynamicAttribution.

/**
 * Atrribution for dynamic sequential scoring; getL1Norm() should agree with
 * getDynamicScoringSequential
 *
 * @param point                   input
 * @param precision               parameter to stop early stopping
 * @param highIsCritical          are high values anomalous (otherwise low
 *                                values are anomalous)
 * @param ignoreLeafMassThreshold we ignore leaves with mass equal/below *
 *                                threshold
 * @param seen                    function for scoring points that have been
 *                                seen before
 * @param unseen                  function for scoring points not seen in tree
 * @param newDamp                 dampening function based on duplicates
 * @return attribution DiVector of the score
 */
public DiVector getApproximateDynamicAttribution(float[] point, double precision, boolean highIsCritical, int ignoreLeafMassThreshold, BiFunction<Double, Double, Double> seen, BiFunction<Double, Double, Double> unseen, BiFunction<Double, Double, Double> newDamp) {
    if (!isOutputReady()) {
        return new DiVector(dimensions);
    }
    VisitorFactory<DiVector> visitorFactory = new VisitorFactory<>((tree, y) -> new DynamicAttributionVisitor(y, tree.getMass(), ignoreLeafMassThreshold, seen, unseen, newDamp), (tree, x) -> x.lift(tree::liftFromTree));
    ConvergingAccumulator<DiVector> accumulator = new OneSidedConvergingDiVectorAccumulator(dimensions, highIsCritical, precision, DEFAULT_APPROXIMATE_DYNAMIC_SCORE_MIN_VALUES_ACCEPTED, numberOfTrees);
    Function<DiVector, DiVector> finisher = vector -> vector.scale(1.0 / accumulator.getValuesAccepted());
    return traverseForest(transformToShingledPoint(point), visitorFactory, accumulator, finisher);
}

Example 2 with DynamicAttributionVisitor

use of com.amazon.randomcutforest.anomalydetection.DynamicAttributionVisitor in project random-cut-forest-by-aws by aws.

the class RandomCutForest method getDynamicAttribution.

/**
 * Same as above, but for dynamic scoring. See the params of
 * getDynamicScoreParallel
 *
 * @param point                   point to be scored
 * @param ignoreLeafMassThreshold said threshold
 * @param seen                    score function for seen points
 * @param unseen                  score function for unseen points
 * @param newDamp                 dampening function for duplicates in the seen
 *                                function
 * @return dynamic scoring attribution DiVector
 */
public DiVector getDynamicAttribution(float[] point, int ignoreLeafMassThreshold, BiFunction<Double, Double, Double> seen, BiFunction<Double, Double, Double> unseen, BiFunction<Double, Double, Double> newDamp) {
    if (!isOutputReady()) {
        return new DiVector(dimensions);
    }
    VisitorFactory<DiVector> visitorFactory = new VisitorFactory<>((tree, y) -> new DynamicAttributionVisitor(tree.projectToTree(y), tree.getMass(), ignoreLeafMassThreshold, seen, unseen, newDamp), (tree, x) -> x.lift(tree::liftFromTree));
    BinaryOperator<DiVector> accumulator = DiVector::addToLeft;
    Function<DiVector, DiVector> finisher = x -> x.scale(1.0 / numberOfTrees);
    return traverseForest(transformToShingledPoint(point), visitorFactory, accumulator, finisher);
}