A survey: Breast Cancer Classification by Using Machine Learning Techniques by Ruaa Hassan Mohammed Ameen, Nasseer Moyasser Basheer, Ahmed Khazal Younis

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Classification of Articles from Mass Media by Categories and Relevance of the Subject Area by Vladislav Dmitrievich Larionov, Ilya Vyacheslavovich Paramonov

“…The research is devoted to classification of news articles about P. G. Demidov Yaroslavl State University (YarSU) into 4 categories: “society”, “education”, “science and technologies”, “not relevant”.The proposed approaches are based on using the BERT neural network and methods of machine learning: SVM, Logistic Regression, K-Neighbors, Random Forest, in combination of different embedding types: Word2Vec, FastText, TF-IDF, GPT-3. …”
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Machine learning and transfer learning techniques for accurate brain tumor classification by Seyed Matin Malakouti, Mohammad Bagher Menhaj, Amir Abolfazl Suratgar

“…Transfer learning applied to image data using a modified GoogLeNet model further enhanced classification accuracy to 99.3 %. These results demonstrate the effectiveness of combining ML and transfer learning techniques for accurate brain tumor classification, addressing limitations of prior approaches and offering improved diagnostic reliability. …”
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Classification of Leguminous Wood Species Based on Small Sample Hyperspectral Images by Hang Su, Shuo Xu, Zhongjian Wang, Wenxin Zhao, Yanan Wen, Lei Zhao

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Weather Classification in West Java using Ensemble Learning on Meteorological Data by Cynthia Nur Azzahra, Yulison Herry Chrisnanto, Gunawan Abdillah

“…This study aims to improve classification accuracy by proposing a stacking classifier approach that combines Support Vector Machine (SVM) and Random Forest as base learners, with Logistic Regression serving as the meta-classifier. …”
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Supervised methods of machine learning for email classification: a literature survey by Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah

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A hierarchical multi-class classification system for face and text datasets by Ashish Saini, Nasib Singh Gill, Preeti Gulia, Khushwant Singh, Fernando Moreira

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Feature Selection Using Pearson Correlation for Ultra-Wideband Ranging Classification by Gita Indah Hapsari, Rendy Munadi, Bayu Erfianto, Indrarini Dyah Irawati

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A Multilevel and Hierarchical Approach for Multilabel Classification Model in SDGs Research by Berliana Sugiarti Putri, Lya Hulliyyatus Suadaa, Efri Diah Utami

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Classification of Heart Failure Using Machine Learning: A Comparative Study by Bryan Chulde-Fernández, Denisse Enríquez-Ortega, Cesar Guevara, Paulo Navas, Andrés Tirado-Espín, Paulina Vizcaíno-Imacaña, Fernando Villalba-Meneses, Carolina Cadena-Morejon, Diego Almeida-Galarraga, Patricia Acosta-Vargas

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An ensemble-driven machine learning framework for enhanced water quality classification by Preet Singh, Taniya Hasija, Salil Bharany, Hafiza Nazra Tun Naeem, B. Chinna Rao, Seada Hussen, Ateeq Ur Rehman

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Thyroid nodule classification in ultrasound imaging using deep transfer learning by Yan Xu, Mingmin Xu, Zhe Geng, Jie Liu, Bin Meng

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Hyperspectral Imaging for Enhanced Skin Cancer Classification Using Machine Learning by Teng-Li Lin, Arvind Mukundan, Riya Karmakar, Praveen Avala, Wen-Yen Chang, Hsiang-Chen Wang

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Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification by Xiaojuan Cai, Ya Zhou, Jie Ren, Jinrong Wei, Shiyu Lu, Hanbing Gu, Weizhe Xu, Xun Zhu

“…We developed five AI models using distinct classification algorithms (Logistic Regression, Support Vector Machine, K-Nearest Neighbor, Random Forest, and Gradient Boosting Machine) that integrate demographic data, cytological findings, and an AI-assisted ultrasound diagnostic system for thyroid nodule assessment. …”
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Classification and Influencing Factors of County Units with Population Shrinkage in Guangdong Province by Chen Tingting, Wu Likun

“…The study also constructed a socioeconomic-natural-demographic indicator system, explored the factors influencing its formation and evolution from the perspective of non-linear influence with the help of a multi-classification logit regression model and a random forest model, and put forward relevant suggestions. …”
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Machine learning classification of consumption habits of creatine supplements in gym goers by Patrícia C. Magalhães, Samuel Encarnação, Andre C. Schneider, Pedro Forte, José Teixeira, Antonio Miguel Monteiro, Tiago M. Barbosa, Ana M. Pereira

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Analysis of risk factors for hypoxemia in PACU for patients undergoing thoracoscopic lung cancer resection based on logistic regression model by Xi Luo, Yanmei Ying, Lu Yin, Pan Chang

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The Threshold Effects of National Governance Quality on the Earnings Management – Performance Nexus: Evidence From Dynamic Panel Threshold Regression by Emmanuel Mensah, Christopher Boachie

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Enhancing Player Experience in a First-Person Shooter with Dynamic Audio Cue Adjustment Based on Gaussian Progress Regression by Xiaoxu Li, Yi Xia, Mustafa Can Gursesli, Xiao You, Siyuan Chen, Ruck Thawonmas

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Trends in hospital admissions and mortality rates for asthma in Ecuador: a joinpoint regression analysis of data from 2000 to 2018 by Philip J Cooper, Alejandro Rodriguez, Natalia Romero-Sandoval, Angelita Cabrera, Sergio Barba

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