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11 results for “Outlier Technique”
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Research ArticleOpen accessEvery word in the titleA Review on Clustering and Outlier Analysis Techniques in DataminingS. Koteeswaran, P. Visu, J. JanetProblem statement: The modern world is based on using physical, biological and social systems more effectively using advanced computerized techniques. A great amount of data being generated by such systems; it leads to a paradigm shift from classical modeling and analyses based on basic principles to developing models and the corresponding analyses directly from data. The ability to extract useful … …American Journal of Applied Sciences, Vol. 9, Issue 2 · 26 Dec 2011 · 7,372 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleNote 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 keywordsDesigning 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
Research ArticleOpen accessIn the abstractA 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 abstractIdentification of Fraud in Accidental and Healthcare Insurance Using Local Outlier Factor: A Machine Learning ApproachJyoti Lele, Vaidehi Deshmukh, Abhinav Chandra, Radhika DesaiAn unsupervised machine learning model that uses the mechanism of the Local Outlier Factor to flag and detect ambiguous as well as potentially fraudulent claims in Accidental and Healthcare insurance is proposed in this paper. It entirely automates the manual investigation of claims by claim appraisers in any organization. The ethos of this model is to comprehensively automate and expedite … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,575 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimizing 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 abstractA 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 abstractElectrophysiology and Biopotential Issues on Human Electrocardiogram: A ReviewMahmoud Ahmed Suliman Ali, Xiao Ping Zeng, Guo Jun LiProblem statement: The heart is the first organ and most importantly to form in the body, where is found the most powerful generator of electromagnetic energy in the human body. Electrophysiology was the best method used to diagnose human heart problem. Knowledge of the electrical potentials in human heart was a quantum leap in the science of the human heart. … …American Journal of Engineering and Applied Sciences, Vol. 4, Issue 3 · 18 Aug 2011 · 7,868 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Logistic Regression to Static Geometric Representation of RatiosAlireza Bahiraie, Noor Akma Ibrahim, A.K.M. Azhar, Ismail Bin MohdProblem statement: Some methodological problems concerning financial ratios such as non-proportionality, non-asymetricity, non-salacity were solved in this study and we presented a complementary technique for empirical analysis of financial ratios and bankruptcy risk. This new method would be a general methodological guideline associated with financial data and bankruptcy risk. Approach: We proposed the use of a new measure of risk, … …Journal of Mathematics and Statistics, Vol. 5, Issue 3 · 30 Sep 2009 · 8,216 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust 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