DEVELOPMENT OF HEALTH INSURANCE CLAIM PREDICTION METHOD BASED ON SUPPORT VECTOR MACHINE AND BAT ALGORITHM by Syaiful Anam, Abdi Negara Guci, Fery Widhiatmoko, Mila Kurniawaty, Komang Agus Arta Wijaya

“…Support Vector Machine (SVM) is one of the superior ML approaches. …”
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Multi-objective portfolio optimization using real coded genetic algorithm based support vector machines by B. Surja, L. Chin, F. Kusnadi

“…Classifying stocks help investors build portfolios that align with their risk profiles and investment goals, in which the model was constructed using the one-versus-one support vector machines method with a radial basis function kernel. …”
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Increasing the degree of acceptability for chatbots in technical support systems for educational sector by using ML and semantic web by Adel A. Bahaddad

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A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…Supervised machine learning algorithms are capable of predicting the remaining useful life (RUL) of a machine. …”
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Early Prediction Detection of Retail and Corporate Credit Risks Using Machine Learning Algorithms by Mohamed A. Hamada, Karim Farag, Adejor E. Abiche

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Advanced Planning Systems in Production Planning Control: An Ethical and Sustainable Perspective in Fashion Sector by Martina De Giovanni, Mariangela Lazoi, Romeo Bandinelli, Virginia Fani

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An Exploratory Application of Machine Learning Algorithms in Estimating Net Salaries in Romania by Adriana Aiftincăi

“…Its practical utility lies in its potential to serve as a forecasting tool for wage policies, a support for employers in budget planning, and a foundation for extending the analysis to regional or sectoral levels. …”
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APPLICATION OF THE SUPPORT VECTOR MACHINE, LIGHT GRADIENT BOOSTING MACHINE, ADAPTIVE BOOSTING, AND HYBRID ADABOOST-SVM MODEL ON CUSTOMERS CHURN DATA by Felice Elena, Robyn Irawan, Benny Yong

“…This paper will use the Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and hybrid Adaptive Boosting-SVM (AdaBoost-SVM) model. …”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Furthermore, the results demonstrate the strong predictive capability of machine learning algorithms in assessing operational risk, highlighting their potential as valuable decision-making tools for risk management in the banking sector.Keywords: Risk Prediction, Operational Risk, Risk Management, Machine Learning IntroductionOperational risk is defined as the risk arising from external factors or failures in internal controls or information systems, which may lead to both anticipated and unexpected losses (Crouchy et al., 1998). …”
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PCA and PSO based optimized support vector machine for efficient intrusion detection in internet of things by Mutkule Prasad Raghunath, Shyam Deshmukh, Poonam Chaudhari, Sunil L. Bangare, Kishori Kasat, Mohan Awasthy, Batyrkhan Omarov, Rajesh R. Waghulde

“…After completing the preparation step, the data set is classified using several machine learning techniques such as support vector machine, linear regression, and random forest. …”
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A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method by Ankit Kumar, Kamred Udham Singh, Manish Kumar

“…We used a dataset with 13 primary characteristics to carry out the research. Support vector machine and logistic regression algorithms are used to process the datasets, and the latter displays the highest accuracy in predicting coronary disease. …”
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Development of a Forecasting Framework Based on Advanced Machine Learning Algorithms for Greenhouse Gas Emissions by Seval Ene Yalçın

“…This paper presents a forecasting framework for greenhouse gas emissions based on advanced machine learning algorithms: multivariable linear regression, random forest, k-nearest neighbor, extreme gradient boosting, support vector, and multilayer perceptron regression algorithms. …”
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Machine learning algorithms for manufacturing quality assurance: A systematic review of performance metrics and applications by Ashfakul Karim Kausik, Adib Bin Rashid, Ramisha Fariha Baki, Md Mifthahul Jannat Maktum

“…However, selecting the most effective ML model remains challenging due to performance variability, scalability constraints, and inconsistent evaluation metrics across manufacturing sectors. This systematic review analyzes over 300 peer-reviewed studies over the last two decades (mostly analyzing the recent works) to evaluate the effectiveness of widely used ML algorithms—Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Random Forests (RFs), Decision Trees (DTs), and K-Nearest Neighbors (KNN)—in QA applications. …”
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Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines by Emmanuel Ahishakiye, Fredrick Kanobe

“…These algorithms are (1) an optimized support vector machine (SVM), and (2) a deep Gaussian Process (DGP) model. …”
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The Application of Support Vector Machine (SVM) in Industrial Carbon Accounting Prediction and Green Electricity Control Strategies by Xu Shasha, Wu Haipeng, Luo Junting, Chen Jian, Jia Huihan

“…This paper, based on the Support Vector Machine (SVM) model, explores its application in industrial carbon accounting, focusing on the interaction between carbon emissions prediction and optimization of control strategies. …”
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A Comparative Study of Loan Approval Prediction Using Machine Learning Methods by Vahid Sinap

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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

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Machine learning approach for optimizing usability of healthcare websites by Amandeep Kaur, Jaswinder Singh, Satinder Kaur

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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…To this purpose, the integration of advanced machine learning algorithms such as cosine similarity, support vector machine, and Naive Bayes improves recommendation systems with sentiment analysis. …”
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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“… Accurately predicting student performance remains a significant challenge in the educational sector. Identifying students who need additional support early can significantly impact their academic outcomes. …”
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