Comparative evaluation of deep learning and machine learning techniques for sentiment analysis of electronic product review data by Nagelli Archana, Saleena B., Prakash B.

“…However, the biggest challenge is the extraction of relevant information from the tremendous data. Machine learning and deep learning techniques have obtained remarkable success in exemplifying and classifying information. …”
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Predictive analytics technique based on hybrid sampling to manage unbalanced data in smart cities by Ayushi Chahal, Preeti Gulia, Nasib Singh Gill, Mohammad Yahya, Mohd Anul Haq, Mohammed Aleisa, Abdullah Alenizi, Arfat Ahmad Khan, Piyush Kumar Shukla

“…This paper proposes a novel predictive analytical technique to manage unbalanced data. A pipeline is designed using Principal Component Analysis (PCA), a hybrid sampling method, and a Machine Learning (ML) prediction method. …”
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Moisture prediction in chicken litter using hyperspectral data and machine learning by Ahmad Tulsi, Abdul Momin, Victoria Ayres

“…This study addresses that gap by evaluating the feasibility of combining HSI with machine learning models to predict moisture content in chicken litter. …”
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Predictive interpretable analytics models for forecasting healthcare costs using open healthcare data by A. Ravishankar Rao, Raunak Jain, Mrityunjai Singh, Rahul Garg

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Machine Learning in the National Economy by Azamjon A. Usmonov

Subjects: “…machine learning…”
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Critical statistical assessment of data in metal additive manufacturing by Raymond Wong, Anh Tran, Bogdan Dovgyy, Claudia Santos Maldonado, Minh-Son Pham

Subjects: “…Data analytics…”
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Revolutionizing educational decision-making: a robust machine learning mechanism for predicting student performance by Muhammad Nadeem Gul, Waseem Abbasi, Muhammad Yaqoob Wani

Subjects: “…Machine learning…”
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Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

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Road Crash Analysis and Modeling: A Systematic Review of Methods, Data, and Emerging Technologies by Lars Skaug, Mehrdad Nojoumian, Nolan Dang, Amy Yap

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A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

“…The efficiency of machine learning (ML) algorithms plays a critical role in their deployment across various applications, particularly those with resource constraints or real-time requirements. …”
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Quantitative Emotional Salary and Talent Commitment in Universities: An Unsupervised Machine Learning Approach by Ana-Isabel Alonso-Sastre, Juan Pardo, Oscar Cortijo, Antonio Falcó

“…This paper examines talent commitment within the university environment, focusing on identifying key factors that influence the loyalty of professors and researchers. To achieve this, machine learning (ML) techniques are employed, as Principal Component Analysis (PCA) for dimensionality reduction and clustering techniques for individual segmentation have been employed in such tasks. …”
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Integrating brain-inspired computation with big-data analytics for advanced diagnostics in neuroradiology by Senthil Kumar, J. Ramprasath, V. Kalpana, Manikandan Rajagopal, Maheswaran S, Rupesh Gupta

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Comparative Analysis of Machine Learning Models for Android Malware Detection by Adem Korkmaz, Selma Bulut

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Comparative Analysis of Machine Learning Algorithms and Statistical Techniques for Data Analysis in Crop Growth Monitoring with NDVI by M. Arunachalam, S. Sekar, A. M. Erdmann, V. V. Sajith Variyar, R. Sivanpillai

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Business Valuation with Machine learning by P. S. Koklev

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Application of machine learning in diabetes prediction based on electronic health record data analysis by Yang Zihan

“…Th is research contributes to the development of machine learning in healthcare, specifically improving disease prediction models through advanced data analysis techniques.…”
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Scalability analysis of heavy-duty gas turbines using data-driven machine learning by Shubhasmita Pati, Julian D. Osorio, Mayank Panwar, Rob Hovsapian

“…While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. …”
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Machine learning and complex network analysis of drug effects on neuronal microelectrode biosensor data by Manuel Ciba, Marc Petzold, Caroline L. Alves, Francisco A. Rodrigues, Yasuhiko Jimbo, Christiane Thielemann

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A Data-Driven Comparative Analysis of Machine-Learning Models for Familial Hypercholesterolemia Detection by Tomasz Kocejko

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Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data by Cemile Gökçe Özmen, Selim Gündüz

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