• Suche: Supervised Machine Learning with Python

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181

Gathering predictors of biodiversity change and reconstructing land cover history in Central Apennines using machine learning and remote sensing data
Makine öğrenimi ve uzaktan algılama verilerini kullanarak Orta Apeninler'deki biyolojik çeşitlilikdeğişiminin tahmin edicilerini toplamak ve manzara geçmişini yeniden oluşturmak
Lemenkova, Polina ; Alma Mater Studiorum Università di Bologna = University of Bologna (UNIBO)
Journal of Anatolian Geography. 2(1):36-47

Artificial Neural Networ... Decision Tree Geospatial Data Ecology Random Forest GIS …
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182

Sentinel-2 Masking CNNs Trained on Physics-Supervised Labels
Efrain Padilla-Zepeda ; Kevin Alonso ; Raquel De Los Reyes ; et al.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 18, Pp 17247-17264 (2025)

Classification algorithm... QC801-809 multispectral sentinel-2 Geophysics. Cosmic physi... deep learning …
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183

Enhancing text generation in joint Nlg/Nlu learning through curriculum learning, semi-supervised training, and advanced optimization techniques.
Shaik, Rahimanuddin
Multimedia Tools & Applications; Sep2025, Vol. 84 Issue 30, p37377-37400, 24p

LANGUAGE models NATURAL language process... DISCOURSE REINFORCEMENT learning WRITTEN communication MACHINE learning …
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184

Atlantic—Automated data preprocessing framework for supervised machine learning
Santos, Luís ; Ferreira, Luís
In Software Impacts September 2023 17

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185

A Novel Developed Supervised Machine Learning System For Classification And Prediction of Software Faults Using NASA Dataset
Nikita Gupta ; Ripu Ranjan Sinha
International Journal on Recent and Innovation Trends in Computing and Communication. 11:715-729

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186

Simulating the rate of prediction error in rainfall big data forecasting.
Pargunaraj, Umaeswari ; Gengi, Geethamahalakshmi ; Narayanaswamy, Hariharan ; et al.
AIP Conference Proceedings. 2025, Vol. 3159 Issue 1, p1-6. 6p.

MACHINE learning SUPERVISED learning DATA mining BIG data DROUGHTS
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187

Using mid-infrared spectroscopy and supervised machine-learning to identify vertebrate blood meals in the malaria vector, Anopheles arabiensis.
Mwanga EP ; Mapua SA ; Siria DJ ; et al.
Publisher: BioMed Central Country of Publication: England NLM ID: 101139802 Publication Model: Electronic Cited Medium: Internet ISSN: 1475-2875 (Electronic) Linking ISSN: 14752875 NLM ISO Abbreviation: Malar J

Animals Blood Chickens blood Feeding Behavior Female Goats blood …
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188

Supervised Machine Learning for Predicting Carbohydrate Malabsorptions Using Hydrogen Breath Tests
Netzer Michael ; Hanser Friedrich ; Ledochowski Maximilian ; et al.
Current Directions in Biomedical Engineering, Vol 8, Iss 2, Pp 285-288 (2022)

03 medical and health sc... carbohydrate malabsorpti... 0302 clinical medicine 0206 medical engineering time classifier Medicine …
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189

Learn the ways of machine learning with Python through one of these 5 courses and specializations.
Fore, Preston
Fortune.com. 3/9/2024, pN.PAG-N.PAG. 1p.

NATURAL language process... ARTIFICIAL intelligence COMPUTER literacy MACHINE learning SUPERVISED learning
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190

Predicting protein interaction network perturbation by alternative splicing with semi-supervised learning
Narykov, Oleksandr ; Johnson, Nathan T. ; Korkin, Dmitry
In Cell Reports 23 November 2021 37(8)

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191

Diagnosing breast cancer subtypes using MRI radiomics and machine learning: A systematic review
Wang, Zhenyue ; Wei, Shulin
In Journal of Radiation Research and Applied Sciences March 2025 18(1)

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192

Predictive model based on Naive Bayes through Supervised Machine Learning and student dropout, in public Technological Education centers in the La Libertad region ; Modelo predictivo basado en Naive Bayes a través de Machine Learning Supervised y la deserción estudiantil, en centros de Educación Tecnológicos públicos de la región La Libertad
Polo Romero, Víctor Jaime
SCIÉNDO INGENIUM; Vol. 20 Núm. 4 (2024): Octubre -Diciembre; 59-71

Algoritmo naive bayes modelo predictivo deserción estudiantil algoritmos supervisados matriz de confusión aprendizaje automático …
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193

Supervised Machine Learning for Predicting Length of Stay After Lumbar Arthrodesis: A Comprehensive Artificial Intelligence Approach.
Etzel CM ; Veeramani A ; Zhang AS ; et al.
Publisher: Wolters Kluwer Country of Publication: United States NLM ID: 9417468 Publication Model: Print Cited Medium: Internet ISSN: 1940-5480 (Electronic) Linking ISSN: 1067151X NLM ISO Abbreviation: J Am Acad Orthop Surg Subsets: MEDLINE

Artificial Intelligence Humans Length of Stay Lumbar Vertebrae surgery Retrospective Studies Supervised Machine Learn... …
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194

Predictive Analytics for House Pricing Using Python and Machine Learning
A Emmanuel Raju
International Journal of Intelligent Systems and Applications in Engineering; Vol. 12 No. 23s (2024); 2367–2374

enhance, algorithms, pro...
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195

A Systematic Review About the Use of Machine Learning Related to Earthquake Studies.
Rosales Huamani, Jimmy ; Ogosi Auqui, Jose ; Ego Aguirre Madrid, Manuel ; et al.
Advances in Civil Engineering; 5/24/2025, Vol. 2025, p1-21, 21p

SUPERVISED learning EARTHQUAKE prediction MACHINE learning RANDOM forest algorithms RESEARCH questions
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196

Capacitive tendency concept alongside supervised machine-learning toward classifying electrochemical behavior of battery and pseudocapacitor materials
Deebansok, Siraprapha ; Deng, Jie ; Le Calvez, Etienne ; et al.
Nature Communications. 15(1):1133-1133

[CHIM]Chemical Sciences
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197

Exploring the role of topological descriptors to predict physicochemical properties of anti-HIV drugs by using supervised machine learning algorithms.
Ahmed, Wakeel ; Zaman, Shahid ; Asif, Eizzah ; et al.
BMC Chemistry; 9/12/2024, Vol. 18 Issue 1, p1-22, 22p

SUPERVISED learning MACHINE learning ANTI-HIV agents MOLECULAR connectivity i... DRUG discovery
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198

BUILDING INTELLIGENT SYSTEMS: PYTHON, MACHINE LEARNING, AND SOFT COMPUTING
Dr. S. Pavani

Machine Learning Neural Networks Intelligent Systems Soft Computing Python
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199

Interpretability of automated machine learning methods in psychological research: A tutorial with AutoGluon in Python.
Fu, Haojie ; Zhao, Xudong
Behavior Research Methods; Nov2025, Vol. 57 Issue 11, p1-16, 16p

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200

GeoTS: A TSC framework for estimating geological formation to model carbon storage reservoirs
Salimath, Shwetha ; Bugiotti, Francesca ; Wlodarczyk, Sylvain ; et al.
SIGKDD. :4773-4783

Toronto, Canada Deep Learning Time serie... Machine Learning • Applied computing → En... Linear algebra algorithm... Feature selection …
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