On the sensitivity of feature ranked lists for large-scale biological data by Danuta Gaweł, Krzysztof Fujarewicz

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Advancing the accuracy of tyrosinase inhibitory peptides prediction via a multiview feature fusion strategy by Watshara Shoombuatong, Nalini Schaduangrat, Nutta Homdee, Saeed Ahmed, Pramote Chumnanpuen

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Digital mapping of soil salinity with time-windows features optimization and ensemble learning model by Shuaishuai Shi, Nan Wang, Songchao Chen, Bifeng Hu, Jie Peng, Zhou Shi

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Prediction model for spontaneous combustion temperature of coal based on PSO-XGBoost algorithm by Hui Zhuo, Tongren Li, Wei Lu, Qingsong Zhang, Lingyun Ji, Jinliang Li

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Research on the Parameter Prediction Model for Fully Mechanized Mining Equipment Selection Based on RF-WOA-XGBoost by Yue Wu, Wenlong Sang, Xiangang Cao, Longlong He

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Machine Learning-Based Normal White Blood Cell Multi-Classification Optimization by Taeyeon Gil, Sukjun Lee, Onseok Lee

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A Novel Hybrid Machine Learning Framework for Wind Speed Prediction by Rhafes Mohamed Yassine, Moussaoui Omar, Raboaca Maria Simona, Mihaltan Traian Candin

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Hybrid Models for Daily Global Solar Radiation Assessment by Abdelkerim Souahlia, Abdelhalim Rabehi, Abdelazize Rabehi

Subjects: “…Solar radiation, renewable energy, features selection, Forecasting, Artificial Neural Networks.…”
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Enhanced Bug Priority Prediction via Priority-Sensitive Long Short-Term Memory–Attention Mechanism by Geunseok Yang, Jinfeng Ji, Jaehee Kim

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An Efficient Malware Detection Approach Based on Machine Learning Feature Influence Techniques for Resource-Constrained Devices by Subir Panja, Subhash Mondal, Amitava Nag, Jyoti Prakash Singh, Manob Jyoti Saikia, Anup Kumar Barman

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A Novel Approach for Stock Price Prediction Using Gradient Boosting Machine with Feature Engineering (GBM-wFE) by Rebwar M. Nabi, Soran Ab. M. Saeed, Habibollah Harron

Subjects: “…Stock Market Forecasting, Feature Engineering Feature Selection Machine Learning Predictive Analysis Predictable Movement Multiclass Classification…”
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Enhanced Grey Wolf Optimization (EGWO) and random forest based mechanism for intrusion detection in IoT networks by Saad Said Alqahtany, Asadullah Shaikh, Ali Alqazzaz

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Electrogastrogram-based detection of cybersickness with the application of wavelet transformation and machine learning: A case study by Ilija V. Tanasković, Nenad B. Popović, Jaka J. Sodnik, Sašo J. Tomažič, Nadica S. Miljković

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Meta Learning Strategies for Comparative and Efficient Adaptation to Financial Datasets by Kubra Noor, Ubaida Fatima

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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

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An Intelligent Big Data Security Framework Based on AEFS-KENN Algorithms for the Detection of Cyber-Attacks from Smart Grid Systems by Sankaramoorthy Muthubalaji, Naresh Kumar Muniyaraj, Sarvade Pedda Venkata Subba Rao, Kavitha Thandapani, Pasupuleti Rama Mohan, Thangam Somasundaram, Yousef Farhaoui

Subjects: “…adabelief exponential feature selection (aefs)…”
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An Efficient Feature Subset Selection Algorithm for Classification of Multidimensional Dataset by Senthilkumar Devaraj, S. Paulraj

“…In this paper, an efficient feature selection algorithm is proposed for the classification of MDD. …”
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Seleksi Fitur dengan Particle Swarm Optimization pada Klasifikasi Penyakit Parkinson Menggunakan XGBoost by Deni Kurnia, Muhammad Itqan Mazdadi, Dwi Kartini, Radityo Adi Nugroho, Friska Abadi

“…The model with feature selection gets an AUC value of 0.9483, while the model without feature selection only gets an AUC value of 0.9366. …”
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Optimization of the Intelligent Sports Health Management System Based on Big Data Technology and Internet of Things by Jian Dang

“…Firstly, a new multilabel feature selection algorithm is proposed in the system analysis layer. …”
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Scalable Multilabel Learning Based on Feature and Label Dimensionality Reduction by Jaesung Lee, Dae-Won Kim

“…A straightforward approach to address this issue is feature selection; however, it may be insufficient to satisfy the practical constraints because the computational cost for feature selection can be impractical when the number of labels is large. …”
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