Performance Analysis and Improvement of Machine Learning with Various Feature Selection Methods for EEG-Based Emotion Classification by Sherzod Abdumalikov, Jingeun Kim, Yourim Yoon

“…We also executed hyperparameter tuning of machine learning algorithms using BO. The performance of each method was assessed. …”
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Comparison of Machine Learning Methods and Ordinary Kriging for Gravimetric Mapping: Application to Yagoua Area (Northern Cameroon) by Mfenjou Martin Luther, Boroh Andre William, Kasi Njeudjang, Kabe Moukete Eric Bruno, Amaya Adama

“…This work focuses on the comparison of a number of machine learning methods (random forest, support vector machine (SVM), and artificial neural networks (ANN)) and ordinary kriging (OK). …”
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Construction of Analogy Indicator System and Machine-Learning-Based Optimization of Analogy Methods for Oilfield Development Projects by Muzhen Zhang, Zhanxiang Lei, Chengyun Yan, Baoquan Zeng, Fei Huang, Tailai Qu, Bin Wang, Li Fu

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Unlocking the secrets of extroverted learners: a mixed-methods dive into English language learning strategies and preferences by Le Thanh Thao, Pham Trut Thuy, Thieu Thi Hai Yen, Nguyen Anh Thi, Phuong Hoang Yen, Huynh Thi Anh Thu, Nguyen Huong Tra

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Automatic identification and characteristics analysis of crack tips in rocks with prefabricated defects based on deep learning methods by Mingtao Gao, Minhui Li, Lu Chen, Zihao Guo, Chengyang Guo, Liping Li, Changsen Bu

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Innovative Learning Approaches in Sports: Comparing Teaching at the Right Level and Classical Methods for Drive Stroke Mastery by Hanik Liskustyawati, Sri Santoso Sabarini, Rony Syaifullah, Waluyo, Agus Mukholid, Baskoro Nugroho Putro, Suratmin

“…This study concludes that the TaRL approach is more effective than the classical method in improving drive stroke skills. These findings underscore the importance of implementing teaching methods tailored to students' abilities to optimize sports learning outcomes. …”
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Recent Advances in Fault Diagnosis Methods for Electrical Motors- A Comprehensive Review with Emphasis on Deep Learning by Jawad Faiz, F. Parvin

“…This paper provides a review of deep learning-based methods for fault diagnosis of electrical motors. …”
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Learning and Evaluation of Dialogue Strategies for New Applications: Empirical Methods for Optimization from Small Data Sets by Verena Rieser, Oliver Lemon

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Modern methods of learning geographical nomenclature using toponymy in the course of «Geography of Russia. Nature and population» at school by T. G. Tuova, F. D. Teuchezh, F. V. Tuguz

Subjects: “…research and partial search methods…”
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CNSW 1.0: Prefectural Reconstruction of China’s Surface Water Resources Using Machine Learning Methods by Qichen Wang, Fubo Zhao, Xi Wang, Wenbo Shi, Yinuo Shan, Qiang Li, Dengfeng Liu, Yiping Wu

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Research on noninvasive electrophysiologic imaging based on cardiac electrophysiology simulation and deep learning methods for the inverse problem by Yi Chang, Ming Dong, Lihong Fan, Bochao Kang, Weikai Sun, Xiaofeng Li, Zhang Yang, Ming Ren

“…This paper aims to provide a new solution for the realization of ECGI by combining simulation model and deep learning methods. Methods A complete three-dimensional bidomain cardiac electrophysiologic activity model was constructed, and simulated electrocardiogram data were obtained as training samples. …”
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Kalman filtering assimilated machine learning methods significantly improve the prediction performance of water quality parameters by Zhenyu Gao, Guoqiang Wang, Jinyue Chen, Lei Fang, Shilong Ren, A. Yinglan, Shuping Ji, Ruobing Liu, Qiao Wang

“…However, existing research on machine learning (ML)-based data assimilation methods remains limited, particularly in terms of addressing the combined impacts of climate change and anthropogenic activities. …”
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Assessing the Level of Employment in the Informal Sector of the Economy of Russian Regions Using Modern Machine Learning Methods by Aleksey Nikolaevich Borisov, Aleksandr Ivanovich Borodin, Roman Vladimirovich Gubarev, Evgeny Ivanovich Dzuyba, Oksana Mikhaylovna Kulikova

“…In the course of solving the classification problem using a modern machine learning method (LightGBM), the key factors affecting the level of employment in the informal sector of the economy of Russian regions were identified. …”
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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

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Generalized MPC-DSVPWM Methods: Reduction Techniques and Explainable Machine Learning With Conformal Prediction for PMSM Drives by Hasan Ali Gamal Al-Kaf, Sadeq Ali Qasem Mohammed, Kyo-Beum Lee

“…Additionally, machine learning methods have been implemented; however, they require complex optimization methods, as the classification number increases exponentially with the level of the inverter. …”
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Predicting and interpreting key features of refractory Mycoplasma pneumoniae pneumonia using multiple machine learning methods by Yuhan Jiang, Xu Wang, Li Li, Yifan Wang, Xuelin Wang, Yingxue Zou

“…Seven mainstream machine learning methods were then employed to construct predictive models, evaluated for reliability and robustness through tenfold cross-validation and sensitivity analysis. …”
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Methodological proposal for the incorporation of the clinical simulation cases to the system of teaching-learning methods in the Pediatric’s rotacional internship by Luis Alberto Corona Martínez, Mercedes Fonseca Hernández, Raúl López Férnandez, Nicolás Ramón Cruz Pérez

“…A methodological proposal is presented for the incorporation of the simulation of clinical cases (through the computer) to the system of teaching-learning’s methods in the Rotational Internship. The proposal is based in three elements: the full correspondence between the proposal; the current tendencies of the medical education; and the principal characteristics that govern the formation of general doctors in Cuba; the pedagogic value of the simulation like teaching method; and the possibilities that the computer offers as medium of teaching. …”
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Correction: An orchestra of machine learning methods reveals landmarks in single-cell data exemplified with aging fibroblasts. by PLOS One Staff

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Comparison of Machine Learning Inversion Methods for Salinity in the Central Indian Ocean Based on SMOS Satellite Data by Ziyi Gong, Hongchang He, Donglin Fan, You Zeng, Zhenhao Liu, Bozhi Pan

“…The Catboost algorithm is introduced for the first time to retrieve sea surface salinity, and a comparison is made with the traditional artificial neural network (ANN) and random forest (RF) machine learning algorithm. The results show that: (1) Through linear fitting with the Argo salinity, the R2 of the three machine learning methods are 0.9299, 0.88 and 0.83, respectively. …”
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Accuracy of machine learning methods in predicting prognosis of patients with psychotic spectrum disorders: a systematic review by Wilson W S Tam, Kang Sim, Jing Ling Tay, Yun Ling Ang

“…Objectives We aimed to examine the predictive accuracy of functioning, relapse or remission among patients with psychotic disorders, using machine learning methods. We also identified specific features that were associated with these clinical outcomes.Design The methodology of this review was guided by the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy.Data sources CINAHL, EMBASE, PubMed, PsycINFO, Scopus and ScienceDirect were searched for relevant articles from database inception until 21 November 2024.Eligibility criteria Studies were included if they involved the use of machine learning methods to predict functioning, relapse and/or remission among individuals with psychotic spectrum disorders.Data extraction and synthesis Two independent reviewers screened the records from the database search. …”
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