ChurnKB: A Generative AI-Enriched Knowledge Base for Customer Churn Feature Engineering by Maryam Shahabikargar, Amin Beheshti, Wathiq Mansoor, Xuyun Zhang, Eu Jin Foo, Alireza Jolfaei, Ambreen Hanif, Nasrin Shabani

“…Additionally, feedback loops are incorporated to validate and enhance the effectiveness of ChurnKB.Integrating knowledge-based features into machine learning models (e.g., Random Forest, Logistic Regression, Multilayer Perceptron, and XGBoost) improves predictive performance of ML models compared to the baseline, with XGBoost’s F1 score increasing from 0.5752 to 0.7891. …”
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Transformation of Geospatial Modelling of Soil Erosion Susceptibility Using Machine Learning by Muhammad Ramdhan Olii, Sartan Nento, Nurhayati Doda, Rizky Selly Nazarina Olii, Haris Djafar, Ririn Pakaya

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Machine Learning Techniques In Wdm-Fso Systems: Comparative Study by Ranim Younes, Mohammad Nassr

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Machine Learning Algorithms in Predicting Prices in Volatile Cryptocurrency Markets by Miguel Jiménez-Carrión, Gustavo A. Flores-Fernandez

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Deepmol: an automated machine and deep learning framework for computational chemistry by João Correia, João Capela, Miguel Rocha

“…Abstract The domain of computational chemistry has experienced a significant evolution due to the introduction of Machine Learning (ML) technologies. Despite its potential to revolutionize the field, researchers are often encumbered by obstacles, such as the complexity of selecting optimal algorithms, the automation of data pre-processing steps, the necessity for adaptive feature engineering, and the assurance of model performance consistency across different datasets. …”
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Machine Learning Applications in Parallel Robots: A Brief Review by Zhaokun Zhang, Qizhi Meng, Zhiwei Cui, Ming Yao, Zhufeng Shao, Bo Tao

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Enhanced Forecasting of Equity Fund Returns Using Machine Learning by Fabiano Fernandes Bargos, Estaner Claro Romão

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Strength prediction of ECC-CES columns under eccentric compression using adaptive sampling and ML techniques by Khaled Megahed

“…Consequently, this study introduces a proposed design that offers competitive performance metrics. The novelty of this work lies in integrating adaptive sampling through Bayesian Optimization (BO) with the power of machine learning (ML) to generate training data that effectively covers a large input space while minimizing error. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

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Machine learning-assisted image analysis techniques for glaucoma detection by Vaibhav Yadav, Barnali Dey, Udayan Baruah, Saumya Das, Om Prakash

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Effective Machine Learning Techniques for Dealing with Poor Credit Data by Dumisani Selby Nkambule, Bhekisipho Twala, Jan Harm Christiaan Pretorius

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Unmasking the Fake: Machine Learning Approach for Deepfake Voice Detection by Muhammad Usama Tanveer Gujjar, Kashif Munir, Madiha Amjad, Atiq Ur Rehman, Amine Bermak

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A review on multi-fidelity hyperparameter optimization in machine learning by Jonghyeon Won, Hyun-Suk Lee, Jang-Won Lee

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Machine learning enabled assessment of the vacuum freeze-drying of the kiwifruit by Uzair Sajjad, Farzana Bibi, Imtiyaz Hussain, Naseem Abbas, Muhammad Sultan, Hafiz Muhammad Asfahan, Muhammad Aleem, Wei-Mon Yan

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Machine Learning for Selecting High-Energy Phosphate Cathode Materials by Yongchun Dang, Zechen Li, Yongchao Yu, Xiwei Bai, Li Wang, Xuelei Wang, Peng Liu, Chen Sun, Xunli Zhou, Zhenpo Wang, Yongjie Zhao, Xiangming He, Lei Li

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Detection of Fake Instagram Accounts via Machine Learning Techniques by Stefanos Chelas, George Routis, Ioanna Roussaki

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Recent advances in ultra-precision machining of lithium niobate crystals by Yebing TIAN, Chengwei WEI, Xiaomei SONG, Cheng QIAN

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Intelligent Assessment of Personal Credit Risk Based on Machine Learning by Chuansheng Wang, Hang Yu

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Springback Prediction of Sandwich Panel Using Machine Learning Methods by Raja Ouled Ahmed Ben Ali, Sami Chatti

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Noise-augmented chaotic Ising machines for combinatorial optimization and sampling by Kyle Lee, Shuvro Chowdhury, Kerem Y. Camsari

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