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375 articles for “classification machine learning”
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Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
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Enhancing Credit Card Fraud Detection Using Device Fingerprinting and Behavioral Biometrics
Abstract: Credit card fraud is a growing global concern, with financial losses projected to reach $ 43.47 billion by 2028. Credit card fraud poses a major challenge in the financial industry, resulting in substantial financial losses and security risks. This research introduces a Machine Learning-based Credit Card Fraud Detection System designed to improve the accuracy of fraud identification. Due to the imbalanced nature of fraud datasets, SMOTE (Synthetic Minority Over-sampling Technique) …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 40–50 Read article
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Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
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The Analysis of Deep Learning-Based Methods for Identifying Diabetic Retinopathy
Abstract: Diabetic retinopathy (DR) is a degenerative eye condition resulting from diabetes mellitus, where high blood glucose levels lead to lesions on the retina. This condition is considered the leading cause of blindness among working-age diabetic patients, particularly in developing countries. As the disease is irreversible, the treatment aims to preserve the patient’s current vision. Early detection is crucial for effective management of DR to maintain vision. One of the main …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 15–31 Read article
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Predict the Severity of Diabetes Cases, Using K-Means and Decision Tree Approach
Abstract: In recent years, diabetes has emerged as one of the most prevalent infections, and its prevalence is rapidly increasing globally. Type 2 diabetes is common throughout the world. For the management and prophylaxis of diabetes, early detection is crucial. Machine Learning (ML) approaches are rapidly gaining importance in the field of diagnostic purposes due to their ability to classify data. In this article, a mixed recommended technique is presented to …
Published in Journal of Advances in Shell Programming · Vol. 9, Issue 2, 2022 · pp. 24–31 Read article
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Maths and Artificial Intelligence: Parallel Yet Intersecting Approach in School Curriculum
Abstract: Understanding students' level of math and working with them in handling their doubts, queries, deciding how they want to approach math, not only as a subject, but a way of interpreting it, thinking, living it, in a less stressed, anxiety and unnecessary troubles around it, which are generally there. We are studying uses of Artificial Intelligence (AI) in diagnosis of current standing of level of math in students and then …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 1, 2023 · pp. 24–30 Read article
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Predicting diabetes status using ensemble algorithms with hyperparameter tuning
Abstract: Diabetes is a condition in which the body is unable to produce enough insulin to keep blood sugar levels under control. If diabetes is not properly identified and treated, it can lead to kidney failure, nerve damage, blindness, and coronary heart disease. A healthy lifestyle, therefore, depends on the early identification of diabetes diseases. However, it can be difficult to assess a person's diabetic status if they live in remote …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 1–9 Read article
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The Significance of Documentation in Library Science: Preserving Knowledge for Future Generations
Abstract: In an era characterized by the relentless march of digital progress, the role of documentation in library science remains a steadfast and essential foundation for the preservation and dissemination of knowledge. This paper delves into the enduring significance of documentation within the field of library science, emphasizing its critical role in safeguarding information for the benefit of future generations. The paper begins by highlighting the historical evolution of documentation practices …
Published in Journal of Advancements in Library Sciences · Vol. 10, Issue 2, 2023 · pp. 45–48 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Machine Learning Based Smart Aquaponics Farming System
Abstract: For many years, researchers have been studying nutrient management in aquaponic systems. Most have concentrated on adequate nutrition control in an aquaponic setup, but there has been relatively little study on commercial scale applications. For plant growth, it is necessary to measure the level of nutrients present in the soil mixture. In our model, the input data was sourced on some interval of time basis from three commercial aquaponic farms. …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 10, Issue 1, 2022 · pp. 30–37 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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A New Evaluation Index for Application of Machine Learning Algorithms to Determine Trust in Skewed Social Media Data
Abstract: In this paper we study the problem of accuracy paradox which arises on the application of machine learning algorithms for inference of trust in skewed social media data. Skewness is defined as the under representation of one class over another in a binary classification problem. We achieved our purpose of identifying the accuracy paradox problem in various algorithms by identifying a new evaluation index called predictive index. The dataset used …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 49–57 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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Comparative Study of Machine Learning Algorithms for Detection of Breast Cancer
Abstract: Breast cancer continues to be the most commonly diagnosed cancer among women, with more than 2.3 million new cases diagnosed yearly worldwide. It is stated as the leading cause of cancer-related deaths. Therefore, this emphasizes the dire necessity for early diagnosis with a view to improving survival. Early diagnosis elevates the effectiveness of prediction and treatment. This research carries out a structured and analytical evaluation of various machine learning algorithms, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 113–129 Read article
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Algorithm for the prediction of cardiovascular disease (CVD)
Abstract: cardiovascular diseases (CVD) still claim a significant number of deaths globally and remain the number one killer with an annual death toll of nearly 17.9 million. While several medical advancements have been made, an early diagnosis is still hard to obtain, which often leads to worsening conditions and intricate treatment options. With the advancement of modern technology, Machine learning has demonstrated to be a miraculous tool which can greatly impact …
Published in Research and Reviews : A Journal of Immunology · Vol. 15, Issue 2, 2025 Read article
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Comparative Study of Data Mining Tools
Abstract: Data mining is a process which finds useful patterns from large amount of data for an appropriate application. It is a well-built technology with great potential to help companies whose focus is on important information in huge databases. It uses machine learning, statistical and visualization technique to discover and predict knowledge in a form which is easily understandable to the user. Classification is important technique of data mining which employs …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 2, 2015 · pp. 35–41 Read article
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Machine Learning Innovations for Effective Spam Comment Filtering in Social Networks
Abstract: The increasing prevalence of social media platforms has revolutionized communication, fostering unparalleled levels of connectivity and data exchange. However, the widespread increase in spam comments presents a serious threat to the integrity of online discussions, potentially undermining the quality of interactions. To confront this issue, our proposed model utilizes machine learning techniques to bolster spam comment detection across various social media platforms. This endeavor involves a thorough investigation encompassing data …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 19–24 Read article
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Heart Disease Prediction Using ANN Based Ensemble Framework (ANNEF) Approach
Abstract: The heart is the most important organ in the human body. One of the deadliest illnesses, heart disease is to blame for countless deaths worldwide. Because of the formation of fatty plaques in arteries, the heart fails to supply enough blood to other body areas to carry out its usual functions in heart disease (atherosclerosis). Age, a sedentary lifestyle, a family history of heart disease, stress, and other factors are …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 9, Issue 3, 2022 · pp. 38–45 Read article
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Medical Image Processing Using Data Science: A Review
Abstract: The purpose of this work is to introduce data science in medical imaging. Both theoretical advancements and real-world applications are covered in this research work. The healthcare industry is distinct from all other industries and is a special sector. It is a top-priority industry that consumes a sizable percentage of the federal budget. In general, only doctors can analyses images, but thanks to technology, we are now able to use …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 7–15 Read article
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An Efficient Deep Learning Classifiers Algorithm for Examining Public Perception of Covid SOPs
Abstract: In December 2019, Wuhan, China, reported the first coronavirus case, confirming the current pandemic. Following that, it swept across the entire world. The leading cause of this disease is still unknown, though. Governments are emphasizing physical distance and wearing masks in public places. The people mostly ignore the safety SOPs, which results in a surge in infected people rates and a healthcare burden on the national economy. Through the identification …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 49–70 Read article