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375 articles for “classification machine learning”
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A Comprehensive Analysis of Classification Methods for Churn Prediction in Financial Services
Abstract: Persistent issues that affect long-term revenue in the banking sector include excessive client attrition. Customary churn models depend on measures related to customer satisfaction, which often result in low predictive accuracy due to their subjective nature. This study proposes an effective early warning model to address customer churn in financial services. Data is preprocessed through cleaning, one-hot encoding, Z-score normalization, and Min-max scaling. To handle class imbalance, the SMOTE algorithm …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 47–61 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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Machine Learning Approaches Towards Resume Classification
Abstract: Finding the right person for an open position can be an unnerving task, especially when there are many applicants, and if the recruiter or the Human Resources department must sort and further categorize all those resumes then it will be a labor-intensive, time-consuming, and tiresome task. Additionally, human assessment of resumes may be biased and prone to mistakes. Manually screening the proper candidate's resume from the pool is not practicable; …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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Methods Based on Machine Learning for Large-scale Classification of Crop Leaf Diseases
Abstract: Worldwide productivity of crops is seriously threatened by crop leaf diseases, which can result in large crop losses and negative economic effects. Effective disease management and crop protection depend on the early and precise detection and classification of these illnesses. Machine learning approaches have gained popularity recently due to their ability to automate procedures related to illness diagnosis and classification. An overview of the several machine learning–based methods used for …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 11–23 Read article
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Integration of Multispectral Satellite data with Ensemble Machine Learning Models for Wetland Classification: a new Ramsar Site in Central India
Abstract: For biodiversity conservation, several wetlands in India have been classified as Ramsar sites, and Sirpur Lake is a recent addition to the list. The objective of this paper is to use Sentinel optical data with 10-meter resolution to prepare a robust and accurate classified map which will be crucial for further analysis. The data on thirteen spectral bands along with four essential spectral indices, Normalized Difference Vegetation Index (NDVI), Normalized …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 Read article
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Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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Classification of Mammogram Images by Machine Learning Algorithm Attacker Nodes
Abstract: Abstract— Breast cancer is basic in ladies' these days. In beginning when cells in the breast start to develop out of control. These cells generally structure a tumor that will frequently be seen on a x-beam or felt as a lump. Cells in almost any piece of the body can move toward becoming malignant growth and can spread to different regions of the body. There are very nearly 6 phases …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 2, 2019 · pp. 1–10 Read article
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Survey of Techniques for Clustering and Classification of ECG using WEKA
Abstract: ECG analysis can be done for automatic detection of abnormality in cardiac activity. This can be helpful in generating alert for saving a precious life. Various techniques have been proposed in literature for feature detection and classification such as; fuzzy logic methods, artificial neural networks (ANN), and support vector machines (SVM), wavelet transform, Hilbert transform, etc. Recently, numerous researches and techniques have been developed for analyzing the ECG signal on …
Published in Journal of Microcontroller Engineering and Applications · Vol. 3, Issue 2, 2016 · pp. 14–19 Read article
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AI-Based Preventive Healthcare Using Quantum Computing
Abstract: With its improved performance and capabilities, quantum machine learning (QML) is becoming a promising field, especially in the healthcare industry for tasks like early heart disease prediction. In this work, a Quantum Support Vector Classifier (QSVC) is proposed as the basic classifier for a bagging ensemble learning model. Shapley Additive explanations (SHAP) are used to evaluate the significance of each attribute in the predictions in order to improve explainability. Using …
Published in Journal of Nanoscience, NanoEngineering & Applications · Vol. 15, Issue 2, 2025 Read article
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Fortifying the Blockchain Fortress: A Machine Learning Paradigm for Enhanced Security
Abstract: Blockchain technology has emerged as a revolutionary tool in the digital landscape, enabling secure and transparent transactions across a decentralized network. Despite its robust security features, blockchain systems remain vulnerable to anomalies and malicious activities. The detection of these anomalies using machine learning has become essential for protecting blockchain networks and ensuring their integrity. This project delves into the application of machine learning techniques to detect abnormal patterns within blockchain …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 33–40 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Artificial Intelligence Based Plant Disease Detection
Abstract: This paper analyses the advanced Neural Network (NN) techniques for hyperspectral data processing, with a particular focus on detecting plant disease. To initiate, we will discuss the NN mechanism, types, models, and classifiers that are used to process the hyperspectral data using different algorithms. Following that, this project discusses the current state of imaging and non-imaging hyperspectral data for early screening and diagnosis of Disease. The NN-hyperspectral hybridization method has …
Published in Recent Trends in Programming languages · Vol. 8, Issue 3, 2021 · pp. 11–24 Read article
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A Comprehensive Method for Sentiment Analysis on Twitter Posts
Abstract: AbstractIn recent years, with ascent of users of social media, researchers get drawn to sentiment analysis. The challenge is that sentiment-dependent info from multiple sources does not seem to be thought of usually in existing sentiment classification techniques. Sentiment analysis is incredibly vital as a result of it helps folks and organizations in their decision-making process. There is vast explosion of “sentiments” on the market from social media like Twitter, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 4, Issue 2, 2017 · pp. 1–5 Read article
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Predicting Client Behavior for Bank Marketing Using Multi-Layer Perceptron Model
Abstract: AbstractThese days machine learning is one of the most widely used approaches in every industry. And among many techniques of machine learning, classification is the most used one. In this paper, various classification models are used to draw some conclusion for many input variables and one output variable of banking data and classify the output variable into two classes. Various statistics are shown which are generated during classification. The work …
Published in Journal of Advancements in Robotics · Vol. 4, Issue 2, 2017 · pp. 5–8 Read article
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Email Spam Classifications Based on Support Vector Machine and Recurrent Neural Network
Abstract: In recent times, e-mail has become one of the fastest and the utmost economical process of communication. Spam emails have dramatically increased over the past few years as a result of the growth in email subscribers. In this growing world, most of the transactions, business, study materials are taking place through emails. But due to the social networks and advertising, some of the emails contain undesirable information known as spam. …
Published in Journal Of Network security · Vol. 10, Issue 2, 2022 · pp. 14–18 Read article
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A Novel Approach to Fingerprint Authentication Using Histogram Oriented Gradients for Feature Extraction and Machine Learning Convolution Neural Network for Classification
Abstract: With applied biometrics, it is possible to identify a person by examining a feature vector of attributes derived from their physical and behaviour characteristics. In biometrics, fingerprints have become one of the most famous and well known techniques of identification and authentication. In light of technological advancements and safety, fingerprint recognition has been successfully used in a variety of Civil, Defence, and Commercial applications for more than a decade. The …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 1–12 Read article
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A Survey on Ensemble Technique for Enhanced Cyberattack Detection
Abstract: It is now more difficult than ever to safeguard enterprises against cyberattacks due to their fast growth and growing sophistication. Stronger cyberattack detection systems are becoming more and more necessary as hostile strategies continue to evolve in order to safeguard information, preserve corporate trust, and protect sensitive data. An overview of contemporary detection techniques is given in this study, with a focus on integrating machine learning (ML) to increase efficacy. …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 50–54 Read article
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Classification Of Music Genre Using Machine Learning
Abstract: Machine Learning is a way that helps the systems to automatically learn from experience and improve the performance and predict the outcome more accurately without any requirement of being explicitly programmed. Music is one of the most significant and influential part of people’s life. Also, music is known as a universal language as it has the power to unite people from different places and cultures. This helps in the recognition …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 1, 2022 · pp. 11–16 Read article
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Identifying COVID-19 in chest X-ray and CT scan images through the application of machine learning algorithms.
Abstract: Since the beginning of the current COVID-19 pandemic, more than five million people have been infected and the numbers are still on the rise. Early symptom detection and proper hygienic standards are thus of utmost importance, especially in venues where people are in random or opportunistic contact with each other. To this end, automated systems with medical-grade body temperature measurement, hygienic compliance evaluation and individualized, person-to-person tracking, are essential, not …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 13–21 Read article