Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…A comparative analysis is presented with a projection based on the Uniform Manifold Approximation and Projection (UMAP) algorithm, showing that MFs had more proximity than the original features when projected, which demonstrates that MFs revealed a clear formation of well-defined clusters, with most points within each group sharing the same color, suggesting greater uniformity in the predicted values. Incorporating these MFs into subsequent regression models demonstrated improved performance, with <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mover><mi>R</mi><mo>¯</mo></mover><mn>2</mn></msup></semantics></math></inline-formula> values higher than 0.9 for MF Grad Boost M3, MF GradientBoost M5, and all kNN MFs and reduced error margins compared to field-measured yield values. …”
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Prediction of knee joint pain in Tai Chi practitioners: a cross-sectional machine learning approach by Yang Chen, Xiaojie Su, Fei Yao, Yushan Liu, Hua Xing, Yubin Ju, Zhiran Kang, Wuquan Sun, Lijun Yao, Li Gong

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Fatigue strength prediction of Cobalt alloys using material composition and monotonic properties: ML-based approach by Subraya Krishna Bhat, Amritanshu Ranjan, Y S Upadhyaya, Vishwanath Managuli

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Prediction of Lubrication Performance of Hyaluronic Acid Aqueous Solutions Using a Bayesian-Optimized BP Network by Xia Li, Feng Guo

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Improving polygenic prediction from summary data by learning patterns of effect sharing across multiple phenotypes. by Deborah Kunkel, Peter Sørensen, Vijay Shankar, Fabio Morgante

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Prediction of water inrush from coal seam floor based on machine learning with small sample data by Chenxi LI, Haifeng LU

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Remaining Useful Life (RUL) Prediction Based on the Bivariant Two-Phase Nonlinear Wiener Degradation Process by Lijun Sun, Yuying Liang, Zaizai Yan

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Integration of clinical and serological biomarkers in a nomogram for predicting interstitial lung disease in idiopathic inflammatory myopathies by Zhixia Wang, Jingyun Zhang, Jin Li, Xiaona Mao, Yangyang Li, Dekun Wang, Wenpeng Ge, Jingzhan Li, Changhua Liang, Zhiqiang Zhang

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The assessment of soil variables relative importance for cereal yield prediction under rainfed cropping system in Morocco by Oumnia Ennaji, Abdellah Hamma, Leonardus Vergütz, Achraf El Allali

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Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning by A. Ahajjam, M. Allgaier, R. Chance, E. Chukwuemeka, J. Putkonen, T. Pasch

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Predicting illness anxiety symptoms based on worry, alexithymia, intolerance of uncertainty and cognitive emotion regulation strategies by Vida Oshrieh, Mohammad Ali Besharat, Masoud Gholamali Lavasani

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A hybrid data-driven method for voltage state prediction and fault warning of Li-ion batteries by Yufeng Huang, Xuejian Gong, Zhiyu Lin, Lei Xu

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Predicting Acute Postoperative Pain Trajectories and Long-Term Outcomes of Adolescents after Spinal Fusion Surgery by Don Daniel Ocay, Mandy M.J. Li, Pablo Ingelmo, Jean A. Ouellet, M. Gabrielle Pagé, Catherine E. Ferland

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Co-pyrolysis of coal-derived sludge and low-rank coal: Thermal behaviour and char yield prediction by Tianli Zhang, Chenxu Zhang, Hai Ren, Zhong Huang, Jun Feng, Na Liu, Rui Li, Yulong Wu

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Heart disease prediction using ECG-based lightweight system in IoT based on meta-heuristic approach by Amin Abbaszadeh, Mahdi Bazargani

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Application of Vis/NIR Spectroscopy in the Rapid and Non-Destructive Prediction of Soluble Solid Content in Milk Jujubes by Yinhai Yang, Shibang Ma, Feiyang Qi, Feiyue Wang, Hubo Xu

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Method and experimental verification of spatial attitude prediction for an advanced hydraulic support system under mining influence by Zhuang Yin, Kun Zhang, ZengBao Zhang, Hongyue Chen, Lingyu Meng, Zhen Wang, Mingchao Du, Xiangpeng Hu, Defu Zhao, Dan Tian

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An approach to predicting linear trends in tagging-related mortality and tag loss during mark-recapture studies by Jasper McCutcheon, Brendan Campbell, Rileigh E. Hudock, Noah Motz, Madison Windsor, Aaron Carlisle, Edward Hale, Edward Hale

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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

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Predicting the compressive strength of concrete incorporating waste powders exposed to elevated temperatures utilizing machine learning by Islam N. Fathy, Hany A. Dahish, Mohammed K. Alkharisi, Alaa A. Mahmoud, Hala Emad Elden Fouad

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