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64 results for “Ensemble Learning”
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Research ArticleOpen accessPhrase in the titleEnsemble Learning for Proactive Detection of Network-Intrusion-Based Insurance FraudBenjamin Asubam Weyori, Selorm Kofi Tagbo et al.We propose an ensemble learning pipeline that proactively integrates Stacking Feature Embedding (SFE) with Principal Component Analysis (PCA) and tree-based ensembles to proactively detect insurance fraud originating from network intrusions. The main contributions are: (1) the novel integration of SFE-PCA as a meta-feature construction step for tabular network flow data; (2) a sensitivity analysis that justifies PCA reduction ratios used … …Journal of Computer Science, Vol. 22, Issue 7 · 16 Jul 2026 · 935 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDevelopment of Customer Predictive Model for Investment Using Ensemble Learning TechniqueThongchai Kaewkiriya, Kittipol WisaengMany new investors that want to purchase a fund might be disappointed with the return-on-investment value. This problem occurs because they do not know important factors that could affect the market value. Plus, some assets might not be suitable for the investor's investment style. To reduce the mentioned problems, many asset management companies research the systems that could find a … …Journal of Computer Science, Vol. 19, Issue 6 · 25 May 2023 · 5,472 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleEnsemble Learning-Based Hybrid Explainable Intrusion Detection System With SMOTE for Enhanced Detection and Interpretability in CybersecurityMohammad Subhi Al-Batah, Taqieddin AldrousWith cyberattacks becoming increasingly sophisticated, there is a growing need for Intrusion Detection Systems (IDS) that are both accurate and interpretable. This study introduces a hybrid IDS framework that integrates Random Forest (RF) and Light Gradient Boosting Machine (LGBM) classifiers with the Synthetic Minority Over-sampling Technique (SMOTE) to address class imbalance. To enhance transparency and trust, the system also incorporates … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,277 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleSmart and Secure Anomaly Detection in IoT Using Quantum Inspired Kernel Ensemble LearningAbrar M. AlajlanThe exponential growth of the Internet of Things networks has greatly increased the attack surface for cyber threats, necessitating the use of strong and perceptive anomaly detection systems. Traditional intrusion detection systems often struggle with high false alarm rates, limited generalization, and inefficiency in processing high-dimensional heterogeneous IoT data. To address this issue, a novel Hybrid Quantum-Enhanced Kernel Ensemble Learning … …Journal of Computer Science, Vol. 22, Issue 3 · 12 Mar 2026 · 1,762 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePM2.5 Prediction Using Homogenous and Heterogenous Ensemble Learning: A Comprehensive EvaluationShrabani Medhi, Minakshi GogoiAir pollution is a global issue. PM2.5 is considered to be the most dangerous pollutant. Prediction of PM2.5 concentration is important so that effective measures can be taken beforehand. A multitude of machine learning methodologies have been employed in forecasting PM2.5 levels, utilizing diverse combinations of ensemble classifiers and regressors. However, there are three important issues that need to be … …Journal of Computer Science, Vol. 20, Issue 9 · 20 Jun 2024 · 5,176 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Active Learning Ensemble Framework for Tropical Crop Yield PredictionAmol Bhilare, Debabrata Swain, Megh Patel et al.Agriculture always has great importance among all different sectors, not only in the world but also in India. It has a significant impact on food security and largely controls the economy. At present, technological advancements have significantly enhanced agricultural productivity, but it can still be further improved by the integration of new cutting-edge techniques like Artificial intelligence. Among the factors … …Journal of Computer Science, Vol. 22, Issue 9 · 11 Sep 2026 · 819 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimization-Based Feature Selection and Ensemble Machine Learning Algorithms for Breast Cancer ClassificationSatyabrata Patro, Jyotirmaya Mishra, Bhavani Sankar PandaBreast cancer, which originates in a woman's breast tissue, is acknowledged to be a significant study topic in the medical field. For a long time, there has been a serious concern with the classification of breast cancer. Thus, to effectively categorize the breast cancer dataset, machine learning methods are designed and implemented. In previous research, the algorithms have classification accuracy … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,172 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCombining 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 · 6,096 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMulti-Source Cyber Intrusion Detection Using Ensemble Machine LearningTaskeen Ali Khan, Sara Abbas, Biswaranjan Senapati et al.The increased usage of digital technologies across businesses has led to an increase in cybercrime. It is difficult for existing intrusion detection systems to detect highly skilled hacking attempts; however, machine learning has been suggested as a way around these drawbacks. The purpose of this study is to evaluate how well various machine learning algorithms identify and stop cyberattacks in … …Journal of Computer Science, Vol. 21, Issue 1 · 14 Dec 2024 · 5,696 accessesView PDFCite