Research ArticleOpen accessEvery word in the titleData Analytics for Imbalanced DatasetMadhura Prabha R, Sasikala SThe primary issue in real-time big data classification is imbalanced datasets. Even though we have many balancing techniques to reduce imbalance ratio which is not suitable for big data that has scalability issues. This study is envisioned to explore different balancing techniques with experimental study. We tried comparing the effectiveness of various balancing strategies, including cutting-edge approaches for severely unbalanced … …Journal of Computer Science, Vol. 20, Issue 2 · 11 Jan 2024 · 5,473 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSENSOR NETWORK PERIODICAL DATA ASSEMBLY USING IMBALANCED CLUSTERING ENERGY EFFICIENT MECHANISMK. Munusamy, R. M.S. ParvathiFast technical advances and development in wireless communication resulted in the huge consumption of wireless sensor networks. The nodes in these networks are ready to be sensed, processing the data and transmitting radio units. While several research works have been conducted related to the power-aware and energy-efficiency using Cooperative Networking protocol (CONET) that reforms clusters but the multiple rate remains … …Journal of Computer Science, Vol. 10, Issue 10 · 28 Jun 2014 · 6,648 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Comparative Analysis of Smote and CSSF Techniques for Diabetes Classification Using Imbalanced DataBashar Hamad Aubaidan, Rabiah Abdul Kadir, Mohamad Taha IjabDiabetes, a prevalent chronic metabolic disorder, poses a significant burden on healthcare systems worldwide. Accurate and timely diagnosis is crucial for effective management and complication prevention. Machine learning presents a promising solution but often faces challenges due to class imbalance within datasets, particularly the underrepresentation of diabetic cases. To address this issue, we introduce Cluster-based Synthetic Sample Filtering (CSSF), a … …Journal of Computer Science, Vol. 20, Issue 9 · 22 Jul 2024 · 4,998 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comparative Study of Resampling, Cost-Sensitive, and Ensemble Techniques for Handling Class Imbalance in Indonesian Financial DataGunawan Kurnia, Ditdit Nugeraha UtamaHandling class imbalance is a critical challenge in machine learning applications, particularly in financial domains where minority instances often represent significant anomalies such as fraud or audit risks. Various oversampling and undersampling methods were tested, alongside cost-sensitive adjustments and ensemble models including Random Forest, AdaBoost, Gradient Boosting, and XGBoost. The evaluation, based on 10-fold stratified cross-validation and performance metrics such … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,874 accessesView PDFCite
Review ArticleOpen accessIn the keywordsAn Insight into Rare Class Problem: Analysis and Potential SolutionsSatyam Maheshwari, R.C. Jain, R.S. JadonThe class imbalance problem presents an important challenge to the data mining community, in which the number of examples of one class is more than the others. This problem is characterized by a different distribution of cases between all the classes. In this paper, our goal is to study the various challenges of class imbalance problem and provide a comparative … …Journal of Computer Science, Vol. 14, Issue 6 · 9 May 2018 · 8,387 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the abstractGeneration Z Health Trends: Data Mining of Sleep and Lifestyle PatternsFrancka Sakti Lee, Johanes Fernandes Andry, Kevin Christianto et al.This study analyzes sleep health and lifestyle data among Generation Z using RapidMiner to identify key issues such as insomnia and stress within this demographic. The research is motivated by the increasing concerns surrounding sleep health and lifestyle choices that significantly impact overall well-being. The primary objective is to identify patterns and correlations in health data to inform targeted interventions … …Journal of Computer Science, Vol. 21, Issue 9 · 19 Oct 2025 · 3,632 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing the CIC IoT Dataset 2023 for Improved Attack Detection through GANs Augmentation and Federated LearningShahad Alahmari, Noura AleisaThe escalating frequency and sophistication of cyber-attacks on Internet of Things (IoT) devices present a pressing challenge to cybersecurity. With IoT device connections projected to exceed 42 billion by 2025, the vulnerability of these devices to cyber-attacks has never been more evident. This paper investigates the integration of Machine Learning (ML) and data augmentation, specifically Generative Adversarial Networks (GAN) and … …Journal of Computer Science, Vol. 21, Issue 7 · 18 Jul 2025 · 9,111 accessesView PDFCite
Research ArticleOpen accessIn the abstractImprovement of Moroccan Dialect Sentiment Analysis Using Arabic BERT-Based ModelsGhizlane Bourahouat, Manar Abourezq, Najima DaoudiThis study addresses the crucial task of sentiment analysis in natural language processing, with a particular focus on Arabic, especially dialectal Arabic, which has been relatively understudied due to inherent challenges. Our approach centers on sentiment analysis in Moroccan Arabic, leveraging BERT models that are pre-trained in the Arabic language, namely AraBERT, QARIB, ALBERT, AraELECTRA, and CAMeLBERT. These models are … …Journal of Computer Science, Vol. 20, Issue 2 · 27 Dec 2023 · 6,545 accessesView PDFCite
Research ArticleOpen accessIn the abstractExploring Data Augmentation for Gender-Based Hate Speech DetectionMuhammad Amien Ibrahim, Samsul Arifin, Eko Setyo PurwantoSocial media moderation is a crucial component to establish healthy online communities and ensuring online safety from hate speech and offensive language. In many cases, hate speech may be targeted at specific gender which could be expressed in many different languages on social media platforms such as Indonesian Twitter. However, difficulties such as data scarcity and the imbalanced gender-based hate … …Journal of Computer Science, Vol. 19, Issue 10 · 29 Sep 2023 · 5,550 accessesView PDFCite