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375 articles for “classification machine learning”
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Comparison of Machine Learning Classification Algorithms for Prediction of Early-stage Diabetes
Abstract: Diabetes is the most widespread and gruesome disease spread all around the globe. It is a chronic metabolic disease which has mild symptoms which are hard to spot at the initial stage. It is well known that diabetes causes a high blood sugar level. This is because insulin is not able to carry sugar from your blood into your cells in order to be stored or used for energy as …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 10, Issue 1, 2023 · pp. 1–5 Read article
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Fault Diagnosis of Air Compressor (AC) System using Local Mean Decomposition (LMD) and Logistic Regression (LR) Machine Learning Classifier
Abstract: This article presents a detailed and systematic procedure for performing fault diagnosis in an air compressor (AC) system by analyzing the audio signals generated during its operation. The analysis covers both normal (healthy) conditions and seven distinct types of faults, including bearing failure, flywheel malfunction, inlet valve leakage, outlet valve leakage, non-return valve failure, piston ring defect, and rider belt issues. To acquire the acoustic signals, the researchers utilized a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 416–427 Read article
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Machine Learning Classification of Normal Versus Age-Related Macular Degeneration OCT Images
Abstract: The macula is a small area of the retina which is especially very important for good eyesight. The age related macular degeneration (AMD) is a type of visual impairment that can cause central vision blur or even loss of visionblindness or even loss of eyesight. AMD was a dangerous and progressing chronic disease which affects people over the age of 60. One of the most common symptoms of this condition …
Published in Journal of Control & Instrumentation · Vol. 13, Issue 3, 2022 · pp. 1–8 Read article
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Prediction of Customer Churn Using Machine Learning Classification Models
Abstract: Customer churn prediction is a critical task in both the telecommunication and medical industries, where retaining customers or patients is essential for ensuring long-term profitability and maintaining high-quality service. To address this, a range of machine learning models—including logistic regression, decision trees, random forests, gradient boosting machines, and support vector machines—were employed to accurately forecast churn behavior. Prior to model training, the dataset underwent thorough preprocessing, which included handling missing …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 86–92 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Prediction of Mobile Phone Price Using Machine Learning Classifiers
Abstract: One cannot imagine one's life without mobile phones; in today's digital era, mobile phones have become a necessity for everyone to fulfil their various demands like messaging, communication, entertainment, productivity, research, shopping and many more. In a thriving market of mobile phones where new smartphones are launched every year with new advanced features and various designs, determining the expense of a mobile can be a trouble-some tasks for consumers. In …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 101–108 Read article
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A Data-Driven Analysis of Machine Learning Classification Models for Reliable Crop Yield Prediction
Abstract: The adoption of ML technologies in agriculture is reshaping farming practices, empowering producers to make informed, data-oriented decisions that improve yields, sustainability, and long-term resilience. In mango cultivation, ML analyzes data from weather, soil, and pests to optimize irrigation, fertilization, and pest control. Predictive analytics help forecast ideal farming practices, minimizing resource wastage and improving yield. Real-time monitoring and image-based disease detection allow timely interventions to maintain plant health and …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 1, 2026 · pp. 12–17 Read article
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Phishing URL Detection Using Machine Learning Classification Algorithms
Abstract: Phishing attack is utilized to get the data like username, secret phrase, financial balance subtleties, and credit card details. Today, is the most well-known cybercrime. Phishing assaults additionally influence the web-based installment area monetary organization, document facilitating or distributed storage, and numerous others. Phishing assault generally focuses to these Web locales which are connected with the internet-based payment area and Web mail. To stop phishing attacks, a variety of methods …
Published in Journal of Web Engineering & Technology · Vol. 9, Issue 3, 2022 · pp. 22–33 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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A Review of Automated Pomegranate Disease Detection and Classification Using Machine Learning
Abstract: The abstract outlines a research study focused on developing an automated system for detecting and classifying diseases that affect pomegranate fruits. Pomegranates, like many other crops, are vulnerable to several types of diseases that appear as visible colored spots on the fruit’s surface. These visible symptoms, such as lesions or discoloration, can significantly impact the fruit’s quality, market value, and yield. Therefore, timely and accurate identification of such diseases is …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 01–13 Read article
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Tensor-Flow Based Approach to Identify Author of the Text
Abstract: Now-a-days a lot of content is available on internet, and people upload lot of information in form of opinion, review, description, recipe etc. online. In such scenario to trace the authenticity of the data, it is necessary to develop an author identification system. It has become a difficult problem in the scope of unnamed information has increased with fast growing Internet life. It is a process to identify author of …
Published in Current Trends in Information Technology · Vol. 8, Issue 3, 2018 · pp. 23–29 Read article
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SATELLITE IMAGE CLASSIFICATION USING MACHINE LEARNING
Abstract: Satellite imagery is used in for various applications such as disaster management, defence, surveys, and environmental understanding. Earlier, manual processing was applied to do analysis. These methods are not accurate to detect the target and classify the object. Hence, in this work machine learning is explored. Now a days deep learning has gain prominence to automate target detection and classification. Convolutional Neural Networks (CNN) are playing vital role in deep …
Published in Journal of Remote Sensing & GIS · Vol. 12, Issue 2, 2021 · pp. 10–18 Read article
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Customer Churn Prediction in Life Insurance
Abstract: In order to forecast customer churn and keep consumers, life insurance firms frequently struggle to use their data efficiently. New opportunities have emerged for tackling this problem due to advancements in categorization models within the field of machine learning. In this study, we suggest an innovative method that uses machine learning classification models to forecast client churn and boost customer retention rates in the life insurance sector. Our proposed system …
Published in E-Commerce for Future & Trends · Vol. 10, Issue 1, 2023 · pp. 23–34 Read article
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Eye Disease Classification Using K-means Clustering Algorithm and Ensemble Classification Approach
Abstract: In this study, we present a comprehensive approach for the classification of eye diseases, specifically targeting normal, cataract, glaucoma, and diabetic retinopathy conditions. This research uses a dataset from Kaggle, which provides a wide and varied collection of retinal images to ensure good representation. The methodology encompasses advanced image processing and machine learning techniques to ensure accurate diagnosis and prediction. The preprocessing phase involves a series of image enhancement techniques …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 15–27 Read article
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A Review on Loan Approval Prediction Based on Machine Learning Techniques
Abstract: The banking industry has also benefited greatly from technological advancements. An increasing number of individuals are submitting loan applications on a daily basis. When deciding which loan applicants to approve, the bank must take certain rules into account. The bank needs to choose the best one for approval based on certain characteristics. The process of carefully verifying every person and recommending them for loan approval is laborious and fraught with …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 2, 2024 · pp. 1–11 Read article
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Monitoring and Controlling System of COVID-19 Symptoms Using Random Forest
Abstract: Corona virus (COVID-19) has already claimed hundreds of lives and infected millions of people around the world. The early detection of COVID-19 is shown in this paper. Machine learning random forest techniques were used to implement the detection procedure on cloud computing. Objectives of the study is to provide health assurance directly from home using some smart tools with cloud computing. Our research contribute the categorization of patients into different …
Published in Research and Reviews : Journal of Computational Biology · Vol. 11, Issue 1, 2022 · pp. 22–29 Read article
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Sentiment Analysis on Financial News Using Deep Learning Algorithm
Abstract: Sentiment analysis is the technique of computationally figuring out and categorizing reviews or comments expressed in a bit of textual content, especially a good way to decide whether or not the writer's mind-set in the direction and also very helpful to identify the customer’s opinion about the particular product or content. It is one of the active and wanted research areas in natural language processing. In existing work, machine learning …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 1, 2021 · pp. 24–27 Read article
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Advances in Lung Cancer Detection and Diagnosis: An Integrative Approach Using Computational Chemistry, Statistics, Bioinformatics, Artificial Intelligence, and Machine Learning
Abstract: Lung cancer is still one of the most common and lethal cancers globally, accounting for more than a million deaths each year. Prompt detection is important, and imaging techniques like chest X-rays, MRIs, PETs, CTs, and molecular imaging have become important tools. But still, even though all these techniques do not provide an accurate classification of the lesion, they have led to the development of computer-based high-resolution image analysis. Computer …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Comprehensive Survey on Intelligent Prognostication of Profitable Farming
Abstract: Nowadays, agriculture has become an important field of research. Particularly, when it comes to crop prediction, agriculture depends on soil, climate, and temperature. Formerly, farmers used to decide which crop to cultivate, what is needed for its growth, and when to harvest it at its best based on their expertise. But due to continuous changes in environmental conditions, it has become very difficult to take any decision related to farming …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 63–69 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article