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42 results for “Outlier”
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Research ArticleOpen accessEvery word in the titleA Robust Modification of the Goldfeld-Quandt Test for the Detection of Heteroscedasticity in the Presence of OutliersMd. Sohel Rana, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: The problem of heteroscedasticity occurs in regression analysis for many practical reasons. It is now evident that the heteroscedastic problem affects both the estimation and test procedure of regression analysis, so it is really important to be able to detect this problem for possible remedy. The existence of a few extreme or unusual observations that we often call … …Journal of Mathematics and Statistics, Vol. 4, Issue 4 · 31 Dec 2008 · 7,936 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleIdentification 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 accessEvery word in the titleMOMENTS OF NONIDENTICAL ORDER STATISTICS FROM BURR XII DISTRIBUTION WITH GAMMA AND NORMAL OUTLIERSZ.A. Al-Saiary, A. A. JamjoomThere are some distributions with no simple closed form for distribution functions such as the Normal and Gamma distributions. This will be the problem if we want to find moments of nonidentical order statistics in the presence of Gamma and Normal outliers observations. We used the idea of approximating Normal and Gamma distributions with Burr type XII distribution. We get … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 12 Apr 2013 · 7,040 accessesView PDFCite
Research ArticleOpen accessEvery word 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 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 keywordsA New Proposed Statistically-Derived Compromise Cut-off CD4 Count Value for HIV Patients to Start using ARVsMaria Mokgadi Lekganyane, Solly Matshonisa SeeletseThe study investigated the relationship between statistical outliers and the inconsistent values of the CD4 count recommended for starting the Antiretroviral Therapy (ART) by HIV-positive patients. Low CD4 counts imply a low immune system. It could be due to AIDS existence or closeness to death. An effective treatment to curb HIV impact is ART, which is recommended for low CD4 … …American Journal of Applied Sciences, Vol. 13, Issue 7 · 29 Jun 2016 · 7,333 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Robust Rescaled Moment Test for Normality in RegressionMd. Sohel Rana, Habshah Midi, A.H.M. Rahmatullah ImonProblem statement: Most of the statistical procedures heavily depend on normality assumption of observations. In regression, we assumed that the random disturbances were normally distributed. Since the disturbances were unobserved, normality tests were done on regression residuals. But it is now evident that normality tests on residuals suffer from superimposed normality and often possess very poor power. Approach: This study … …Journal of Mathematics and Statistics, Vol. 5, Issue 1 · 31 Mar 2009 · 8,260 accessesView PDFCite
Research ArticleOpen accessIn the keywordsGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,575 accessesView PDFCite