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63 articles for “Classifiers Performance”
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Research ArticleOpen accessIn the abstractImproved Intrusion Detection System to Alleviate Attacks on DNS ServiceHani Mahmoud Al-Mimi, Nesreen Adnan Hamad, Mosleh Mohammad Abualhaj et al.Cybercriminals continuously devise new and more sophisticated ways to attack their targets’ security and cyberattacks are on the rise. One of the earliest and most vulnerable network services is the Domain Name System (DNS), which has had several security issues that have been repeatedly exploited over time. Building a strong Intrusion Detection System (IDS) that guards against unwanted access to … …Journal of Computer Science, Vol. 19, Issue 12 · 9 Nov 2023 · 5,789 accessesView PDFCite
Research ArticleOpen accessIn the abstractHuman Age Predication from Face Images Based on Combining Deep Wavelet Network and Machine Learning AlgorithmsZahraa Salam Abu Ghrban, Nidhal K. EL AbbadiDue to the numerous variances in face appearance, age estimation using facial images is a difficult subject. Many factors can affect the estimation of human age such as race, face post, gender, lifestyle, etc. By considering more factors, the optimum performance may be obtained. In this study, we proposed a method to predict the age of facial images. The proposed … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 5,573 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Machine Learning-Based Algorithms to Predict the Early Childhood Development Among Under Five Children in BangladeshMd. Ismail Hossain, Iqramul Haq, Ashis Talukder et al.In this research, an effort has been made to apply a number of classifiers to predict Early Child Development (ECD) in the context of Bangladesh using the Bangladesh multiple indicator cluster survey, 2019 data set (i.e., to evaluate which sort of algorithm best identifies ECDI). To predict the ECD, nine well-known machine learning algorithms were applied, including Linear Regression (LR), … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 6,850 accessesView PDFCite
Research ArticleOpen accessIn the abstractCombining SMOTE and OVA with Deep Learning and Ensemble Classifiers for Multiclass ImbalancedRattanawadee PanthongThe classification of real-world problems alwaysconsists of imbalanced and multiclass datasets. A dataset having unbalanced andmultiple classes will have an impact on the pattern of the classification modeland the classification accuracy, which will be decreased. Hence,oversampling method keeps the class of dataset balanced and avoids theoverfitting problem. The purposes of the study were to handle multiclassimbalanced datasets and to improve … …Journal of Computer Science, Vol. 18, Issue 8 · 23 Aug 2022 · 6,099 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Integration for Precise Facial Micro-Expression RecognitionViola Bakiasi Shtino, Markela Muça, Senada BushatiThis study advances facial micro-expression recognition through innovative machine-learning techniques, addressing critical needs in psychology, security, and human-computer interaction. The purpose of this study is to improve micro-expression recognition through the optimization of feature transformation and machine learning algorithms. We introduce a novel approach combining Kernel Principal Component Analysis (KPCA) and Uniform Manifold Approximation and Projection (UMAP) for dimensionality reduction, … …Journal of Computer Science, Vol. 20, Issue 11 · 22 Oct 2024 · 5,601 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoft Marking Scheme of SVM Hierarchical Classifiers for Attack ClassificationAzizi Abdullah, Warhamni Jani@MokhtarClassification is a predictive modelling problem that involves assigning a class label to an instance correctly. There exist several strategies in machine learning to deal with the multi-class classification problems for attack detection. One of the popular strategies is the one-vs-one that decomposes the multi-class problem into multiple binary ones. The approach has been applied in many popular supervised learning … …Journal of Computer Science, Vol. 17, Issue 9 · 27 Sep 2021 · 6,006 accessesView PDFCite
Research ArticleOpen accessIn the abstractSentimental Analysis on Health-Related Information with Improving Model Performance using Machine LearningWael M.S. Yafooz, Abdullah AlsaeediSocial media platforms are extensively used in exchanging and sharing information and user experience, thereby resulting in massive outspread and viewing of personal experiences in many fields of life. Thus, informative health-related videos on YouTube are highly perceptible. Many users tend to procure medical treatments and health-related information from social media particularly from YouTube when searching for chronic illness treatments. … …Journal of Computer Science, Vol. 17, Issue 2 · 22 Feb 2021 · 7,466 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassification of Heart Disease Using Cluster Based DT LearningSenthilkumar Mohan, Chandrsegar Thirumalai, Abdalah RababahIn the rural side, due to the absence of cardiovascular ailment centers, around 12 million people passing away worldwide reported by WHO. The principal purpose of coronary illness is a propensity of smoking. Our Cluster based disease Diagnosis (CDD) applies the ML classifiers to improve the prediction accuracy of cardiovascular diseases. For this we have taken a real Cleveland dataset … …Journal of Computer Science, Vol. 16, Issue 1 · 10 Jan 2020 · 7,367 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Study of Data Mining Classification Techniques for Detection and Prediction of Phishing WebsitesLuai Al-ShalabiData mining is the process of discovering or extracting information from large amount of data that are stored in databases or datasets such as phishing dataset. Phishing is a vital web security problem that involves simulating legitimate websites to mislead online users in order to steal their sensitive information. This paper aims to detect and predict the type of the … …Journal of Computer Science, Vol. 15, Issue 3 · 19 Mar 2019 · 7,478 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Classification Models for Predicting Mortality Rate Using Thyroid Cancer DataNorah Saleh AlghamdiMachine Learning (ML) can potentially enhance predictions in real-life domains. This study presents an evaluation and comparison of different ML methods which can be applied on thyroid cancer dataset, called Prostate, Lung, Colorectal and Ovarian (PLCO), of approximately 155,000 participants with thyroid cancer occurrence and mortality incidence. The ML models are explored for predicting mortality rates of patients with thyroid … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 7,796 accessesView PDFCite