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10 results for “outlier detection”
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Research ArticleOpen accessPhrase in the titleFast Algorithms for Outlier DetectionFawaz A.M. Masoud, Moh'd B. Al- Zoubi, Imad Salah, Ali Al-DahoudFinding fast algorithms to detect outliers (as unusual objects) by their distance to neighboring objects is a big desire. Two algorithms were proposed to detect outliers quickly. The first was based on the Partial Distance (PD) algorithm and the second was an improved version of the PD algorithm. It was found that the proposed algorithms reduced the number of distance … …Journal of Computer Science, Vol. 4, Issue 2 · 28 Feb 2008 · 7,041 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleRobust Outlier Detection in Linear RegressionNethal K. Jajo, Xizhi WuNew methodology of robust outlier detection based on Robustly Studentized Robust Residuals (RSRR) examination is well established in linear regression analysis. Two new robust location estimators of linear regression parameters are developed in simple and multiple cases. Based on these robust estimators we obtain RSRR. We used RSRR to derive a new measure of distance to be used in outlier … …American Journal of Applied Sciences, Vol. 1, Issue 2 · 30 Jun 2004 · 6,933 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Misuse and Anomaly Intrusion Detection System Using Hybrid Supervised and Unsupervised Data Mining ApproachesHoma Molavi, Mohammad KhanbabaeiIntrusion Detection Systems (IDSs) play a crucial role in monitoring computer network security. Data mining and machine learning techniques facilitate the identification of intrusion patterns within large volumes of data. Hybrid data mining models have become increasingly popular in IDSs due to their enhanced effectiveness. This study presents a novel hybrid IDS that combines misuse and anomaly detection by integrating … …Journal of Computer Science, Vol. 22, Issue 6 · 6 Jul 2026 · 999 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptimizing Mobile Edge Computing Efficiency through Multidimensional Generative Adversarial NetworkAnitha Premkumar, Sowmya Vemagal Lakshminarayana, Shankar Rajagopal et al.Big data Processing and the IoT have recently gained popularity as study topics in MEC and thorough research is sought for well-informed decisions. Mobile edge equipment, such as base stations, routers, and edge servers, usually have limited processing capabilities compared to traditional data centers. According to this perspective, this research constructs MEC using Intelligent Outlier Detection with a Multidimensional Generative … …Journal of Computer Science, Vol. 21, Issue 2 · 18 Jan 2025 · 4,686 accessesView PDFCite
Research ArticleOpen accessIn the keywordsNote on the Comparison of Some Outlier Labeling TechniquesN. P. OlewueziProblem statement: Methods proposed for estimating and resolving outliers are compared. Approach: In this respect, we exploit three well-known classifiers for identifying outliers to establish guidelines for the choice of outlier detection methods. Results: It was shown that the standard deviation is inappropriate to use here because it is highly sensitive to extreme values. Conclusion/Recommendations: The result of these estimated … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 18 Nov 2011 · 8,261 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Fast Distance-Based Algorithm to Detect OutliersMoh’d Belal Al-Zoubi, Nadim ObeidvA fast distance-based algorithm for outlier detection will be proposed. It was found that the proposed algorithm reduced the number of distance calculations compared to the nested-loop algorithm. Test results were performed on different well-known data sets. The results showed that the proposed algorithm gave a reasonable amount of CPU time saving. …Journal of Computer Science, Vol. 3, Issue 12 · 31 Dec 2007 · 6,732 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Novel Anomaly Detection Approach for Nifty Stocks using Machine Learning for Construction of Efficient Portfolio to Reduce Losses and Protect GainsVirrat Devaser, Priyanka ChawlaMachine Learning is the most essential and widely utilized methodological approach these days for performing, organizing, and analyzing data using a variety of approaches to produce correct and efficient results. Machine learning methodologies are also applicable to stock markets, which have grown multi-fold in recent years, and with the amount of money involved, the possibility of manipulation is always present … …Journal of Computer Science, Vol. 18, Issue 5 · 6 Jun 2022 · 6,443 accessesView PDFCite
Research ArticleOpen accessIn the abstractBayesian Changepoint Analysis of the Extreme Rainfall EventsWan Zawiah Wan Zin, Abdul Aziz Jemain, Kamarulzaman IbrahimProblem statement: This study assesses recent changes in extremes of annual rainfall in Peninsular Malaysia based on daily rainfall data for 50 rain-gauged stations over the period 1975-2004. Approach: Eight indices that represent the extreme events are defined and analyzed, which are extreme Dry Spell (XDS), extreme Rain-Sum (XRS), extreme wet-day intensities at 95% and 99% percentiles (I95 and I99), … …Journal of Mathematics and Statistics, Vol. 8, Issue 1 · 6 Feb 2012 · 7,250 accessesView PDFCite
Research ArticleOpen accessIn the abstractTwo-Step Robust Diagnostic Method for Identification of Multiple High Leverage PointsArezoo Bagheri, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: High leverage points are extreme outliers in the X-direction. In regression analysis, the detection of these leverage points becomes important due to their arbitrary large effects on the estimations as well as multicollinearity problems. Mahalanobis Distance (MD) has been used as a diagnostic tool for identification of outliers in multivariate analysis where it finds the distance between normal … …Journal of Mathematics and Statistics, Vol. 5, Issue 2 · 30 Jun 2009 · 8,306 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDesigning a Generic Information Systems Audit Framework to Improve the Quality of Audit in Higher EducationElfadil A. Mohamed, Elgilani El. Elshareif, Omer Ishag Eldai MohamedThere are some similarities between Financial Statement Audit (FSA) and Information Systems Audit (ISA). FSA is an examination of the reliability and integrity of financial statement records, whereas ISA is a review and evaluation of the controls, risks and system development within an information systems infrastructure to ensure that the safeguards protect against abuse, protect assets, maintain data integrity and … …Journal of Computer Science, Vol. 15, Issue 5 · 10 May 2019 · 7,857 accessesView PDFCite