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RODHA: Robust Outlier Detection using Hybrid Approach

A. Mira, D.K. Bhattacharyya, S. Saharia
2012 American Journal of Intelligent Systems  
In this paper, we have developed a robust supervised outlier detection algorith m using hybrid approach (RODHA) which incorporates both the concept of distance and density along with entropy measure while  ...  Detection of such outliers is fundamental to a variety of database and analytic tasks such as fraud detection and customer migration.  ...  Furthermore, the incorporation of entropy for outlier detection makes it more robust and sensitive than other existing outlier detection techniques.  ... 
doi:10.5923/j.ajis.20120205.07 fatcat:3fgv6fnnjzheho3bmr5c6lnlja

Circulating and Excreted Corticosteroids and Metabolites, Hematological, and Serum Chemistry Parameters in the Killer Whale (Orcinus orca) Before and After a Stress Response

K. J. Steinman, T. R. Robeck, G. A. Fetter, T. L. Schmitt, S. Osborn, S. DiRocco, H. H. Nollens, J. K. O'Brien
2020 Frontiers in Marine Science  
A stress test was performed in 13 zoo-based killer whales (Orcinus orca) whereby animals were elevated out of the water on a rising lift-bottom platform for 20 min.  ...  Paired blood and feces were tested for cortisol, corticosterone, aldosterone, and their metabolites and hematological and serum chemistry parameters.  ...  Funder also provided support in form of salary for authors KS, TR, TS, SO, SD, HN, and JO.  ... 
doi:10.3389/fmars.2019.00830 fatcat:mkai64vcfrgl7m5beasb246zpi

On Detecting Clustered Anomalies Using SCiForest [chapter]

Fei Tony Liu, Kai Ming Ting, Zhi-Hua Zhou
2010 Lecture Notes in Computer Science  
Detecting local clustered anomalies is an intricate problem for many existing anomaly detection methods.  ...  Clustered anomalies are able to avoid detection since they defy these assumptions by being dense and, in many cases, in close proximity to normal instances.  ...  This analysis confirms that SCiForest is robust in detecting dense global anomaly clusters even when they are large and dense. SVM's result is omitted for clarity.  ... 
doi:10.1007/978-3-642-15883-4_18 fatcat:tdd42unwnvb5vol7ykwnvx2fvi

SDCOR: Scalable Density-based Clustering for Local Outlier Detection in Massive-Scale Datasets [article]

Sayyed Ahmad Naghavi Nozad and Maryam Amir Haeri and Gianluigi Folino
2021 arXiv   pre-print
This paper presents a batch-wise density-based clustering approach for local outlier detection in massive-scale datasets.  ...  Finally, by another scan of the entire dataset and using a suitable criterion, an outlying score is assigned to each object called SDCOR (Scalable Density-based Clustering Outlierness Ratio).  ...  Hodge (University of York, UK) for her clever advice on the title of this paper, and Dr.  ... 
arXiv:2006.07616v11 fatcat:t63z5vrgqjhrdosewdozvjh3ku

Class separation through variance: a new application of outlier detection

Andrew Foss, Osmar R. Zaïane
2010 Knowledge and Information Systems  
Experiments show that FASTOUT typically outperforms other state-of-the-art outlier detection methods on high dimensional data such as Feature Bagging, SOE1, LOF, ORCA and Robust Mahalanobis Distance, and  ...  This paper introduces a new outlier detection approach and discusses and extends a new concept, class separation through variance.  ...  This results in a large cluster being discovered and is an unnecessary cost for outlier detection. Since all attributes are binned, this issue extends to all attribute types.  ... 
doi:10.1007/s10115-010-0347-3 fatcat:7hkaueergrhyhd4dnmtpapoelu

Fast and Scalable Outlier Detection with Metric Access Methods [chapter]

Altamir Gomes Bispo Junior, Robson Leonardo Ferreira Cordeiro
2019 Lecture Notes in Computer Science  
For outlier detection, both training and testing instances are used, totalizing 7200 instances, but with only 6 real attributes.  ...  KNN-Outlier is the basis for many other works, such as Orca (BAY; SCHWABACHER, 2003) and RBRP (GHOTING; PARTHASARATHY; OTEY, 2008).  ... 
doi:10.1007/978-3-030-22741-8_14 fatcat:j3ewkkip5va6vckbo2yz7rjzra

HiCS: High Contrast Subspaces for Density-Based Outlier Ranking

Fabian Keller, Emmanuel Muller, Klemens Bohm
2012 2012 IEEE 28th International Conference on Data Engineering  
and provides enhanced quality for outlier ranking.  ...  Measuring the contrast of such subspaces for outlier rankings is an open research challenge.  ...  All of these techniques focus on the related domain of subspace clustering. They try to decouple the detection of clusters and the selection of individual subspaces for each cluster.  ... 
doi:10.1109/icde.2012.88 dblp:conf/icde/KellerMB12 fatcat:ouotyhngrnaglcoi5g23ij7dqi

Multiple kernel learning for heterogeneous anomaly detection

Santanu Das, Bryan L. Matthews, Ashok N. Srivastava, Nikunj C. Oza
2010 Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '10  
We pose a general anomaly detection problem which includes both discrete and continuous data streams, where we assume that the discrete streams have a causal influence on the continuous streams.  ...  These parameters may be continuous measurements or binary or categorical measurements recorded in one second intervals for the duration of the flight.  ...  Kanishka Bhaduri for valuable discussions and suggestions. The authors also thank the reviewers for providing input to improve the paper.  ... 
doi:10.1145/1835804.1835813 dblp:conf/kdd/DasMSO10 fatcat:5ixu26suuva3lec3j2jfnxeyy4

A review of novelty detection

Marco A.F. Pimentel, David A. Clifton, Lei Clifton, Lionel Tarassenko
2014 Signal Processing  
Bay and Schwabacher [157] introduced the distance-based outlier detection algorithm called "ORCA".  ...  The proposed method was applied to novelty detection, and benefited from the robustness of the L1 norm to outliers. Perera et al.  ... 
doi:10.1016/j.sigpro.2013.12.026 fatcat:ha6kc4bzhbajxbo2mdyh5cw5hu

Cranial shape correlates with diet specialization in northeast Pacific killer whale (Orcinus orca) ecotypes [article]

Charissa W. Fung
2016
Resident, transient (Bigg's), and offshore killer whales (Orcinus orca) live in sympatric and parapatric ranges in the northeast Pacific Ocean.  ...  I found that transient (Bigg's) killer whales that bite and tear apart large mammals have more robust cranial skeletons than the piscivorous resident and offshore killer whales that handle smaller prey  ...  Lance Barrett-Lennard showed great faith in me from the very beginning and I am so grateful for his talent, mentorship, and friendship. Dr.  ... 
doi:10.14288/1.0314137 fatcat:sym5a5jzdnbslchctowpikrq54

Interface '99

Arnold Goodman
2000 SIGKDD Explorations  
This personal overview of Interface '99 is intended to communicate its meaning and relevance to SIGKDD, as well as provide valuable information on trends within the Interface for data miners seeking to  ...  In addition, it is the newest link in a bridge between the Interface and KDD begun by References 2-4 and the sessions on KDD at Interface '98 and Interface '99.  ...  coefficients, and for aiding the detection of outliers by writing the minimization problem as an integer program.  ... 
doi:10.1145/846183.846207 fatcat:ncoticeezndhpknzyx3huk66hu

Recent Advances in Anomaly Detection Methods Applied to Aviation

Luis Basora, Xavier Olive, Thomas Dubot
2019 Aerospace (Basel)  
After a brief introduction to the main traditional data-driven methods for anomaly detection, we review the recent advances in the area of neural networks, deep learning and temporal-logic based learning  ...  Anomaly detection is an active area of research with numerous methods and applications.  ...  [10] provide a general overview of the state-of-the-art methods for anomaly detection in graph data.  ... 
doi:10.3390/aerospace6110117 fatcat:kprkb643xrhcnmjy2c2lbzoa7m

An automatic feature generation approach to multiple instance learning and its applications to image databases

Hao Cheng, Kien A. Hua, Ning Yu
2009 Multimedia tools and applications  
Specifically, the feature vectors of the image bags are grouped into clusters and each cluster is given a label.  ...  Data mining can then be employed to uncover common label patterns for each image category.  ...  In our proposal, we used the Orca package (http://www.isle.org/∼sbay/ software/orca/) for outlier detection, and the number of nearest neighbors K o used to detect outliers was set to be 5, and the top  ... 
doi:10.1007/s11042-009-0335-3 fatcat:carlhvvzpvdebi3ctbkmeb2ebi

Age-related micro-RNA abundance in individual C. elegans

Mark Lucanic, Jill Graham, Gary Scott, Dipa Bhaumik, Christopher C. Benz, Alan Hubbard, Gordon J. Lithgow, Simon Melov
2013 Aging  
The major exception to this was mir-71, which increased in abundance with age and was required for normal longevity.  ...  We screened miRNA levels for age-related changes in individual worms and investigated their influence on the lifespan of the nematode C. elegans.  ...  ACKNOWLEDGEMENTS We thank Carl Hansen for help with the protocol for preparation of C. elegans for single worm analysis of miRNA expression. We are grateful to the members of  ... 
doi:10.18632/aging.100564 pmid:23793570 pmcid:PMC3824409 fatcat:ahup73mjw5duzdptm56euztiaq

An Automatic Attribute Based Access Control Policy Extraction from Access Logs [article]

Leila Karimi, Maryam Aldairi, James Joshi, Mai Abdelhakim
2021 arXiv   pre-print
An attribute-based access control (ABAC) model provides a more flexible approach for addressing the authorization needs of complex and dynamic systems.  ...  The proposed approach employs an unsupervised learning-based algorithm for detecting patterns in access logs and extracting ABAC authorization rules from these patterns.  ...  graph).  ... 
arXiv:2003.07270v4 fatcat:nwl62malmndmpgz34liabt3emm
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