• LOF

  • Referenced in 88 articles [sw19311]
  • density-based local outliers. For many KDD applications, such as detecting criminal activities ... common patterns. Existing work in outlier detection regards being an outlier as a binary property...
  • mvBACON

  • Referenced in 26 articles [sw36501]
  • methods, the computation cost often makes outlier detection unattractive. All multiple outlier detection methods have ... this paper (algorithms for the detection of outliers in multivariate and regression data). The algorithms...
  • MOA

  • Referenced in 40 articles [sw11966]
  • machine learning algorithms (classification, regression, clustering, outlier detection, concept drift detection and recommender systems...
  • LIBRA

  • Referenced in 28 articles [sw10553]
  • Regression (RSIMPLS), classification (RDA, RSIMCA), clustering, outlier detection for skewed data (including the bagplot based ... provided for model checking and outlier detection. Most of the functions require the MATLAB Statistics...
  • Rainbow

  • Referenced in 32 articles [sw01263]
  • sets for functional data display and outlier detection...
  • MVN

  • Referenced in 15 articles [sw20752]
  • graphical approaches and implements multivariate outlier detection and univariate normality of marginal distributions through plots...
  • GET

  • Referenced in 15 articles [sw35164]
  • functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction...
  • robCompositions

  • Referenced in 12 articles [sw11804]
  • methods to impute rounded zeros, (robust) outlier detection for compositional data, (robust) principal component analysis...
  • ELKI

  • Referenced in 12 articles [sw30860]
  • unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance...
  • mvoutlier

  • Referenced in 6 articles [sw11289]
  • package mvoutlier: Multivariate outlier detection based on robust methods. various methods for multivariate outlier detection...
  • FUNTA

  • Referenced in 5 articles [sw23476]
  • multivariate functional pseudo-depth for shape outlier detection, JMVA 146, 325-340, detecting shape outliers in functional data is presented ... compare its performance with respect to outlier detection in simulation studies and a real data...
  • SOREX

  • Referenced in 5 articles [sw10972]
  • data. However, focusing only on the detection of outliers these approaches miss to provide reasons ... outlier rankings. To enable exploration of subspace outliers and to complete knowledge extraction we provide ... information in addition to the pure detection of outliers. As wittinesses for the outlierness...
  • ROBPCA

  • Referenced in 67 articles [sw11592]
  • computed rapidly, and is able to detect exact-fit situations. As a by-product, ROBPCA ... diagnostic plot that displays and classifies the outliers. We apply the algorithm to several datasets...
  • ICSOutlier

  • Referenced in 3 articles [sw18258]
  • package ICSOutlier: Outlier Detection Using Invariant Coordinate Selection. Multivariate outlier detection is performed using invariant...
  • CerioliOutlierDetection

  • Referenced in 3 articles [sw11068]
  • CerioliOutlierDetection: Outlier detection using the iterated RMCD method of Cerioli (2010). This package provides ... method of Cerioli (2010) for multivariate outlier detection via robust Mahalanobis distances. It also provides...
  • OutlierD

  • Referenced in 3 articles [sw27832]
  • Bioconductor/R package OutlierD: Outlier detection using quantile regression on the M-A scatterplots of high ... throughput data. This package detects outliers using quantile regression on the M-A scatterplots...
  • HighDimOut

  • Referenced in 2 articles [sw27459]
  • package HighDimOut: Outlier Detection Algorithms for High-Dimensional Data. Three high-dimensional outlier detection algorithms ... this package. The angle-based outlier detection (ABOD) algorithm is based on the work ... Schubert, and Zimek [2008]. The subspace outlier detection (SOD) algorithm is based on the work ... Zimek [2009]. The feature bagging-based outlier detection (FBOD) algorithm is based on the work...
  • robustlmm

  • Referenced in 4 articles [sw23530]
  • linear mixed-effects models often contain outliers or other contamination. Even little contamination can drive ... contamination has only little influence and to detect and flag contamination. We introduce ... assess the model fit, how to detect outliers, and how to compare different fits...
  • ContaminatedMixt

  • Referenced in 9 articles [sw21014]
  • approach also allows for automatic detection of mild outliers via the maximum a posteriori probabilities...
  • OutlierLib

  • Referenced in 2 articles [sw22689]
  • OutlierLib - A MATLAB Library for OutliersDetection. The article presents a library of MATLAB functions ... implement the widely used algorithms of outlier detection. The library includes the outlier tests ... review of the methods for detecting and treating outliers...