Distance-based outlier detection algorithms, such as DBOutlier and kNN. For methods based on local density, see package
Class Summary Class Description AbstractDBOutlier<O>Simple distance based outlier detection algorithms. AbstractDBOutlier.Par<O>Parameterization class. DBOutlierDetection<O>Simple distanced based outlier detection algorithm. DBOutlierDetection.Par<O>Parameterization class. DBOutlierScore<O>Compute percentage of neighbors in the given neighborhood with size d. DBOutlierScore.Par<O>Parameterization class. HilOut<O extends NumberVector>Fast Outlier Detection in High Dimensional Spaces HilOut.HilFeatureHilbert representation of a single object. KNNDD<O>Nearest Neighbor Data Description. KNNDD.Par<O>Parameterization class. KNNOutlier<O>Outlier Detection based on the distance of an object to its k nearest neighbor. KNNOutlier.Par<O>Parameterization class. KNNSOS<O>kNN-based adaption of Stochastic Outlier Selection. KNNWeightOutlier<O>Outlier Detection based on the accumulated distances of a point to its k nearest neighbors. KNNWeightOutlier.Par<O>Parameterization class. LocalIsolationCoefficient<O>The Local Isolation Coefficient is the sum of the kNN distance and the average distance to its k nearest neighbors. LocalIsolationCoefficient.Par<O>Parameterization class. ODIN<O>Outlier detection based on the in-degree of the kNN graph. ReferenceBasedOutlierDetectionReference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points. ReferenceBasedOutlierDetection.ParParameterization class. SOS<O>Stochastic Outlier Selection.
Enum Summary Enum Description HilOut.ScoreTypeType of output: all scores (upper bounds) or top n only