• Suche: Supervised Machine Learning with Python

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161

Employing advanced supervised machine learning approaches for predicting micronutrient intake status among children aged 6-23 months in Ethiopia.
Zemariam AB ; Adisu MA ; Habesse AA ; et al.
Publisher: Frontiers Media S. A Country of Publication: Switzerland NLM ID: 101642264 Publication Model: eCollection Cited Medium: Print ISSN: 2296-861X (Print) Linking ISSN: 2296861X NLM ISO Abbreviation: Front Nutr Subsets: PubMed not MEDLINE

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162

Supervised Machine Learning Classification Algorithms for Detection of Fracture Location in Dissimilar Friction Stir Welded Joints
Mishra, Akshansh ; Vats, Apoorv
Fracture and Structural Integrity; Vol. 15 No. 58 (2021): October 2021; 242-253 ; Frattura ed Integrità Strutturale; V. 15 N. 58 (2021): October 2021; 242-253 ; 1971-8993

Fracture Location Machine Learning Friction Stir Welding Artificial Intelligence Python Programming
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163

Designing a TPMS metamaterial via deep learning and topology optimization.
Viswanath, Asha ; Abueidda, Diab W. ; Modrek, Mohamad ; et al.
Frontiers in Mechanical Engineering; 2024, p1-18, 18p

UNIT cell SUPERVISED learning PYTHON programming langu... FINITE element method MINIMAL surfaces
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164

Development and predictive modeling of PLLA/gelatin nanofibers with functionalized CNTs for bone tissue engineering
Negaresh, Hakimeh ; Bahrami, S. Hajir ; Nazarpak, Masoumeh Haghbin ; et al.
In Materials Today Communications January 2026 50

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165

TrackSegNet:A tool for trajectory segmentation into diffusive states using supervised deep learning
Kabbech, Hélène ; Smal, Ihor ; Kabbech, Hélène ; et al.
Kabbech, H & Smal, I 2024, 'TrackSegNet : A tool for trajectory segmentation into diffusive states using supervised deep learning', Journal of Open Source Software, pp. 1-4. <

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166

Predictive analytics on crop yield using supervised learning techniques.
Okesola, Julius Olatunji ; Ifeoluwa, Olaniyi ; Ajagbe, Sunday Adeola ; et al.
Indonesian Journal of Electrical Engineering & Computer Science; Dec2024, Vol. 36 Issue 3, p1664-1673, 10p

MACHINE learning CROP yields AGRICULTURAL productivit... FARM produce WEATHER forecasting PYTHON programming langu...
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167

Understanding the Sequential Pathways of Punitive Supervision and Employee Outcomes: Applying Hayes’ PROCESS Macro With Supervised Machine Learning
Saira Ahmed ; Sadia Farooq ; Ghulam Abid ; et al.
Human Behavior and Emerging Technologies. 2025

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169

Predicting major adverse cardiovascular events after orthotopic liver transplantation using a supervised machine learning model: A cohort study
Soldera, Jonathan ; Corso, Leandro Luis ; Rech, Matheus Machado ; et al.
World J Hepatol

0301 basic medicine 0303 health sciences 03 medical and health sc... Retrospective Cohort Stu...
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170

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171

SHAZAM: Self-Supervised Change Monitoring for Hazard Detection and Mapping
Samuel Garske ; Konrad Heidler ; Bradley Evans ; et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 15456-15476 (2025)

FOS: Computer and inform... QC801-809 Computer Vision and Patt... Geophysics. Cosmic physi... Image and Video Processi... Computer Science - Compu... …
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172

libcll: an Extendable Python Toolkit for Complementary-Label Learning
Ye, Nai-Xuan ; Mai, Tan-Ha ; Wang, Hsiu-Hsuan ; et al.

Computer Science - Machi... Computer Science - Artif... Computer Science - Compu...
Report
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173

Enhancing Text Generation in Joint NLG/NLU Learning Through Curriculum Learning, Semi-Supervised Training, and Advanced Optimization Techniques
Shaik, Rahimanuddin ; Kishore, Katikela Sreeharsha

Computer Science - Compu... Computer Science - Artif... Computer Science - Machi...
Report
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174

Prediction of Compressive Strength of Fly-Ash-Based Concrete Using Ensemble and Non-Ensemble Supervised Machine-Learning Approaches
Yang Song ; Jun Zhao ; Krzysztof Adam Ostrowski ; et al.
Applied Sciences, Vol 12, Iss 1, p 361 (2021)

fly ash concrete ensemble modeling cross-validation python Technology …
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176

MyESL: A Software for Evolutionary Sparse Learning in Molecular Phylogenetics and Genomics.
Sanderford M ; Sharma S ; Stecher G ; et al.
Publisher: Oxford University Press Country of Publication: United States NLM ID: 8501455 Publication Model: Print Cited Medium: Internet ISSN: 1537-1719 (Electronic) Linking ISSN: 07374038 NLM ISO Abbreviation: Mol Biol Evol Subsets: MEDLINE

Machine Learning Models, Genetic Phylogeny Software Genomics methods Evolution, Molecular
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177

Rectified linear unit-based deep learning model for ferromagnetic blood flow under magnetohydrodynamic and radiation effects
Louati, Hanen ; Shah, Zahoor ; Zahoor Raja, Muhammad Asif ; et al.
In Journal of Radiation Research and Applied Sciences September 2025 18(3)

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178

Prediction of Lung Cancer Disease Using Machine Learning Techniques
Rukhsar Hatam Qadir ; Karwan Mohammed HamaKarim
UHD Journal of Science and Technology, Vol 8, Iss 2, Pp 75-83 (2024)

machine learning Science data analysis data mining techniques classifiers supervised machine learn... …
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179

Track classification in Active Target Time Projection Chamber using supervised machine learning methods.
Das, Pralay Kumar ; Majumdar, Nayana ; Mukhopadhyay, Supratik
EPJ Web of Conferences. 10/7/2025, Vol. 337, p1-7. 7p.

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180

Integrating and reporting full multi-view supervised learning experiments using SuMMIT
Bauvin, Baptiste ; Corbeil, Jacques ; Benielli, Dominique ; et al.

Benchmarking Multimodal Reproducible Research Modularity Interpretability [INFO.INFO-LG] Computer... …
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