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71 articles for “Random Forest Model”
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Research ArticleOpen accessIn the abstractA Novel Approach for Differentiating AI-Generated and Real Images Using Gabor and Color Layout Filters (GF and CLF)G. Ayyappan, A. Thankaraj, S. Surendran et al.The emergence of generative AI images has profoundly upended the art world. Distinguishing AI-generated images from human-created artwork is increasingly challenging. If this issue remains unresolved, dishonest individuals may exploit those who are willing to pay more for original artwork and businesses whose stated policies exclude AI graphics. There are a number of methods for differentiating AI photos from human … …Journal of Computer Science, Vol. 22, Issue 2 · 3 Mar 2026 · 1,751 accessesView PDFCite
Research ArticleOpen accessIn the abstractCRISP-DM-Based Mobile Application for Predicting High-Crime Areas in Metropolitan LimaHugo Vega Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza et al.The city of Lima, Peru, has been facing a serious climate of citizen security that has risen extremely high in recent years. The objective of this work is to identify and predict areas of high crime incidence through a mobile application based on historical data on criminal incidents recorded by users. The mobile application has been implemented using the CRISP-DM … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,972 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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
Research ArticleOpen accessIn the abstractA Metaheuristic-Optimized Feature Selection for Early-Stage Diabetes Prediction With SHAP-Guided Insight into Influential AttributesEsmay Azam Rochy, Jannatul Ferdaus, Uzzal Biswas et al.Diabetes is a metabolic disorder that causes elevated blood glucose. This long-term health condition can lead to cardiovascular diseases, stroke, kidney failure, visual impairment, neuropathy, and even death in critical cases. So, a Computer-Aided Diagnostic (CAD) system is necessary to diagnose diabetes automatically. A clinician can utilize a machine learning-based CAD system that automatically diagnoses many people. This paper will … …Journal of Computer Science, Vol. 22, Issue 2 · 24 Feb 2026 · 1,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn AI-Powered Integrated Care Model Combining Traditional Chinese Medicine and Western Medicine for Personalized Alzheimer’s Disease ManagementShurong Li, Yiming Chen, Jin Xu et al.Alzheimer's Disease (AD) gradually reduces memory and cognition. While Western medicine focuses on pharmacological treatments, it frequently ignores holistic factors such as mood and digestion. Traditional Chinese Medicine (TCM) addresses these issues through a wellness-oriented approach. However, the combination of both systems in patient care is uncommon. Current Alzheimer's disease treatments are often siloed, relying solely on Western or alternative … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 2,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Hybrid Machine and Deep Learning Model for Detecting Arabic Phishing EmailsFahad GhabbanPhishing emails are becoming an increasingly popular type of cybercrime on the internet, affecting both businesses and individuals. The attackers generally use various methods to trick victims and extract personal information from them, such as bank details, home addresses, and account information. Many attempts have been proposed to tackle this issue by using filtering mechanisms or automated classification methods which … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,897 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Analytics and Procurement Visibility: A Big-Data-Driven Approach to Customer Satisfaction in Supply Chain ManagementDevendra Nath Pathak, Rakesh Kumar Yadav, Hitendra SinghIn the current dynamic and consumer driven market environment, supply chains need to move out of reactive to the proactive ecosystems. One of the most urgent requirements is increasing procurement visibility and the development of better order planning for the inventory to meet the products’ demand with continued high customer satisfaction. This paper is an agenda of big-data-driven predictive analytics … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,442 accessesView PDFCite
Research ArticleOpen accessIn the abstractCuckoo Search Optimized Random Forest for Breast Cancer PrognosisPrasad S. Sase, Debabrata Swain, Shailesh KumarBreast cancer remains a major global health concern due to its high mortality rate, particularly when diagnosis occurs at an advanced stage. Accurate and early differentiation between benign and malignant tumors is therefore critical for improving patient outcomes. Conventional diagnostic practices largely depend on manual assessment and clinical expertise, which may lead to subjective variability in decision-making. To overcome this … …Journal of Computer Science, Vol. 22, Issue 1 · 31 Jan 2026 · 2,098 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid Parallel Framework Utilizing Machine and Deep Learning for Rapid Rumor Detection in Social MediaNeetu Rani, Amit Kumar Bhardwaj, Shaily Jain et al.Numerous businesses have faced significant repercussions due to the widespread dissemination of false information and rumors across social media platforms. The impact of fake news extends to tarnishing public perception, damaging corporate reputations, disrupting communities, undermining governmental integrity, exposing companies to risks, and posing a grave threat to social cohesion. This research article delves into the endeavours of prominent researchers … …Journal of Computer Science, Vol. 21, Issue 12 · 27 Jan 2026 · 1,814 accessesView PDFCite