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290 articles for “Machine Learning Model”
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Research ArticleOpen accessIn the abstractA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 924 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Novel Crow Search Optimization Based Feature Selection With Optimal DNN for Big Data ClassificationC. Mahesh, J. Ruby Elizabeth, S. Gnana Selvan et al.Big data analytics has become popular due to its applicability in various real-time applications. To attain better performance, big data can be analyzed using the machine learning and deep learning models at recent times, various domains have started to deal with big dataset which involves numerous sets of features. Repetitive and unwanted features, which reduces the classification performance can be … …Journal of Computer Science, Vol. 22, Issue 6 · 30 Jun 2026 · 1,257 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Machine Learning Techniques to Analyze Consumer Mindset Metrics Embedded in Arabic Dialect Texts Across Social Media PlatformsSafa Khaled Al Sarairah, Mohd Heikal Husin, Noor Farizah IbrahimAs social media grows in popularity around the world, analyzing Arabic texts on these platforms can provide important insights into consumer attitudes and behavior. The complexity and diversity of Arabic and its dialects, however, make it a challenging task. This research raises these challenges by using and comparing the performance of Machine Learning (ML) models for classifying social media comments … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Sentiment Analysis for Malayalam With mBERT: A Profoundly Transparent and Accurate Approach Using LIMEAnitha R., K. S. Anil Kumar, Rajeev R. R. et al.The overlapping sentiment boundaries, intensifiers, and intricate morphological structures in Malayalam present particular difficulties for sentiment analysis, making it hard for traditional machine learning techniques to produce consistent results. We present an explainable sentiment analysis framework in this paper that refines a Multilingual Bidirectional Encoder Representations from Transformers (mBERT) model on a novel constituency-level dataset that has been manually curated … …Journal of Computer Science, Vol. 22, Issue 5 · 2 Jun 2026 · 1,065 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnsemble 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 · 1,284 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Adversarial Attacks: ML Techniques, Classification and CountermeasuresBhavesh Kumar Sharma, Sanatan Ratna, Rajiv KumarMachine Learning (ML) and Deep Learning (DL)-based technologies have made significant strides in areas such as computer vision, natural language processing, and autonomous systems. Yet they have been applied in high-stake applications, and have been found to be fragile through adversarial attacks-, maliciously crafted small distortions that fool models into making mistakes. From the pioneering work by Szegedy et al. … …Journal of Computer Science, Vol. 22, Issue 5 · 19 May 2026 · 1,511 accessesView PDFCite
Research ArticleOpen accessIn the abstractAssessing the Comparative Effectiveness of Ensemble CatBoost Versus XGBoost Models in Predicting Heart Disease OutcomesManivannan D., G. Gifta Jerith, G. Chandra Sekhar et al.Cardiovascular Diseases (CVDs) are a common form of heart disease that remains a significant global cause of mortality, responsible for more than 30% of all fatalities. Without intervention, the global fatality count is projected to reach 22 million by 2030. Arterial plaque buildup may impede blood flow, potentially causing heart attacks or strokes. A combination of risk causes, including lack … …Journal of Computer Science, Vol. 22, Issue 4 · 4 May 2026 · 1,552 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,853 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrated Machine Learning Framework for Citrus Grading and Yield Prediction Using Classifier-Informed RegressionLydia Dede Obeng, Isaac O. OsunmakindeAgriculture remains a cornerstone of human sustenance, yet accurate citrus fruit grading and yield predictions remain significant challenges due to visual similarities between varieties such as oranges and grapefruits. This includes the inefficiencies of manual grading. This study presents a new dual-function machine learning system that integrates classification and regression to simultaneously grade citrus fruits and forecast crop yields. This … …Journal of Computer Science, Vol. 22, Issue 4 · 24 Apr 2026 · 1,898 accessesView PDFCite
Research ArticleOpen accessIn the abstractMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,333 accessesView PDFCite