Výsledky vyhledávání - lazy supervised algorithm

Companion: A Social Support Generating Application for Lonely and Socially Isolated Individuals using Lazy Supervised Algorithm

Autoři: Marisa Buctuanon Xavier Comabig Wavina Vivienne Mayola

Zdroj: Recoletos Multidisciplinary Research Journal, Vol 8, Iss 1, Pp 97-111 (2020)

Témata: H1-99, HF5001-6182, social isolation, lazy supervised algorithm, knn, 1. No poverty, 3. Good health, instance-based algorithm, Social sciences (General), 03 medical and health sciences, 0302 clinical medicine, social support group, loneliness, T1-995, Business, 10. No inequality, Technology (General)

Přístupová URL adresa: https://rmrj.usjr.edu.ph/rmrj/index.php/RMRJ/article/download/863/210
https://doaj.org/article/111957c32a5d495fa265d5b016614b2f
https://doi.org/10.32871/rmrj2008.01.07
https://rmrj.usjr.edu.ph/rmrj/index.php/RMRJ/article/view/863
https://rmrj.usjr.edu.ph/rmrj/index.php/RMRJ/article/download/863/210
https://www.safetylit.org/citations/index.php?fuseaction=citations.viewdetails&citationIds[]=citjournalarticle_666504_13

Comparison of supervised ML algorithms for road traffic crash prediction models in Rwanda.

Autoři: Jean de Dieu, Gatesi Bin, Shuai Huang, Wencheng a další

Zdroj: Transport. Apr2025, Vol. 178 Issue 2, p83-98. 16p.

Témata: *MACHINE learning, *TRAFFIC accidents, *ROAD safety measures, *MATHEMATICAL variables, *TRAFFIC accident statistics, *SUPERVISED learning

Geografický termín: RWANDA

Analysis Of Supervised Learning Approaches For Identification Of Oral Squamous Cell Carcinoma: A Multimodal Approach.

Autoři: Mandal, Rupesh Prasad, Ankit Anwar, Dilshad a další

Zdroj: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 4, p5299-5309, 11p

Témata: SUPERVISED learning, IMAGE recognition (Computer vision), SUPPORT vector machines, RANDOM forest algorithms, DECISION trees

A hybrid technique for arabic text classification using semi-supervised learning.

Autoři: Alfartosy, Hadeel H. Khafaji, Hussein K.

Zdroj: AIP Conference Proceedings; 2024, Vol. 3097 Issue 1, p1-18, 18p

Témata: SUPERVISED learning, SECURE Sockets Layer (Computer network protocol), CLASSIFICATION, MACHINE learning, AUTODIDACTICISM

Comparison of result of machine learning algorithms in predicting heart disease.

Autoři: Yousefi, Sajad Poornajaf, Maryam

Zdroj: Frontiers in Health Informatics; 2023, Vol. 12, p1-10, 10p

Témata: MACHINE learning, SUPERVISED learning, HEART diseases, RANDOM forest algorithms, PYTHON programming language, HEART disease diagnosis

A study of instance-based algorithms for supervised learning tasks : mathematical, empirical, and psychological evaluations

Autoři: Aha, David W.

Popis souboru: application/pdf

Přístupová URL adresa: https://escholarship.org/uc/item/3tr7k5g6
https://escholarship.org/content/qt3tr7k5g6/qt3tr7k5g6.pdf

Novel Biomarker Prediction for Lung Cancer Using Random Forest Classifiers.

Autoři: C, Lavanya S, Pooja Kashyap, Abhay H a další

Zdroj: Cancer Informatics; 4/21/2023, p1-15, 15p

Témata: SMALL cell lung cancer, LOGISTIC regression analysis, LUNG cancer, NON-small-cell lung carcinoma, RANDOM forest algorithms, SUPERVISED learning

Novel Biomarker Prediction for Lung Cancer Using Random Forest Classifiers.

Autoři: Lavanya C. Pooja S. Kashyap, Abhay H. a další

Zdroj: Cancer Informatics; Jan-Dec2023, Vol. 22, p1-15, 15p

Témata: SMALL cell lung cancer, LUNG cancer, NON-small-cell lung carcinoma, RANDOM forest algorithms, SUPERVISED learning, MACHINE learning, NAIVE Bayes classification

Retinal Microvascular Characteristics—Novel Risk Stratification in Cardiovascular Diseases.

Autoři: Rusu, Alexandra Cristina Brînzaniuc, Klara Tinica, Grigore a další

Zdroj: Diagnostics (2075-4418); May2025, Vol. 15 Issue 9, p1073, 11p

Témata: CORONARY artery bypass, MACHINE learning, DISEASE risk factors, OPTICAL coherence tomography, ARTIFICIAL intelligence

Comprehensive Review On The Analysis Of Various Machine Learning Algorithms For Early Detection Of Critical Diseases.

Autoři: Chitre, Divya Bhushan, Shivendu Patil, Manisha S.

Zdroj: Journal of Advanced Zoology. 2024 Supplement, Vol. 45, p65-72. 8p.

Stack Coupling Machine Learning Model Could Enhance the Accuracy in Short-Term Water Quality Prediction.

Autoři: Zhang, Kai Xia, Rui Wang, Yao a další

Zdroj: Water (20734441); Oct2025, Vol. 17 Issue 19, p2868, 29p

Témata: WATER quality, MACHINE learning, PREDICTION models, NONPOINT source pollution, LONG short-term memory, BOOSTING algorithms, WATERSHEDS, RUNOFF

Geografický termín: SOUTHEAST China

Adaptability of regression algorithms to protein Plant behavior

Additional Titles: Adaptabilidad de algoritmos de regresión al comportamiento de las plantas proteicas

Autoři: Uvidia-Cabadiana, Hernán A. Estrada-Jiménez, Pedro M. Herrera-Herrera, Rocio del Carmen a další

Zdroj: Enfoque UTE; Preprint; Enfoque UTE; Ahead-of-print (Preprint); 1390-6542; 1390-9363; 10.29019/enfoqueute.vn

Témata: Metabolitos secundarios, modelos de regresión, pared celular, valor nutritivo, Secondary metabolites, regression models, Secondary metabolites; regression models; cell wall; nutritional value., nutritional value, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion

URL: https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944

Adaptability of regression algorithms to the behavior of protein plants

Additional Titles: Adaptabilidad de algoritmos de regresión al comportamiento de las plantas proteicas

Autoři: Uvidia-Cabadiana, Hernán A. Estrada-Jiménez, Pedro M. Herrera-Herrera, Rocio del Carmen a další

Zdroj: Enfoque UTE; Vol. 14 Núm. 2 (2023); pp. 20-34; Enfoque UTE; Vol. 14 No. 2 (2023); pp. 20-34; 1390-6542; 1390-9363; 10.29019/enfoqueute.v14n2

Témata: Metabolitos secundarios, modelos de regresión, pared celular, valor nutritivo, Secondary metabolites, regression models, Secondary metabolites; regression models; cell wall; nutritional value., nutritional value, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion

URL: https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/952
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/953
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/963
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/952
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/953
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/963

Adaptability of regression algorithms to the behavior of protein plants

Additional Titles: Adaptabilidad de algoritmos de regresión al comportamiento de las plantas proteicas

Autoři: Uvidia, Hernán Estrada-Jiménez, Pedro M. Herrera-Herrera, Rocio del Carmen a další

Zdroj: Enfoque UTE; Vol. 14 Núm. 2 (2023); pp. 20-34; Enfoque UTE; Vol. 14 No. 2 (2023); pp. 20-34; 1390-6542; 1390-9363; 10.29019/enfoqueute.v14n2

Témata: Secondary metabolites, regression models, Secondary metabolites; regression models; cell wall; nutritional value., nutritional value, Metabolitos secundarios, modelos de regresión, pared celular, valor nutritivo, info:eu-repo/semantics/article, info:eu-repo/semantics/publishedVersion

URL: https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/952
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/953
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/963
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/944
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/952
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/953
https://ingenieria.ute.edu.ec/enfoqueute/index.php/revista/article/view/861/963

Metaheuristic-Driven Optimization for Efficient Resource Allocation in Cloud Environments.

Autoři: Chitradevi, B. Mercy, A. Immaculate Ramasrinivasan, Shanmugam a další

Zdroj: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 2, p2927-2942, 16p

Témata: METAHEURISTIC algorithms, RESOURCE allocation, CLOUD computing, STIMULUS & response (Psychology)

Current insights on predicting vestibular diseases using machine learning.

Autoři: SÖYLEMEZ, Emre ŞEKER, Muhammed Mustafa

Zdroj: Turkish Journal of Medical Sciences; 2025, Vol. 55 Issue 5, p1077-1087, 11p

A Robustness Evaluation of Machine Learning Algorithms for ECG Myocardial Infarction Detection.

Autoři: Sraitih, Mohamed Jabrane, Younes Hajjam El Hassani, Amir

Zdroj: Journal of Clinical Medicine; Sep2022, Vol. 11 Issue 17, p4935, 23p

Témata: MACHINE learning, SUPERVISED learning, MYOCARDIAL infarction, SUPPORT vector machines, K-nearest neighbor classification

Machine Learning Models of the Geospatial Distribution of Groundwater Quality: A Systematic Review.

Autoři: Mehrabi, Mohammad Polya, David A. Han, Yang

Zdroj: Water (20734441); Oct2025, Vol. 17 Issue 19, p2861, 48p

Témata: MACHINE learning, GROUNDWATER quality, STATISTICAL reliability, PREDICTION models, SPATIAL variation, ENVIRONMENTAL risk assessment, POLLUTANTS

Open science perspectives on machine learning for the identification of careless responding: A new hope or phantom menace?

Autoři: Alfons, Andreas Welz, Max

Zdroj: Social & Personality Psychology Compass; Feb2024, Vol. 18 Issue 2, p1-21, 21p

Témata: MACHINE learning, OPEN scholarship, SUPERVISED learning, DATA libraries, EVALUATION methodology

TRAFFIC VOLUMES PREDICTION USING BIG DATA ANALYTICS METHODS.

Autoři: Janković, Slađana Uzelac, Ana Zdravković, Stefan a další

Zdroj: International Journal for Traffic & Transport Engineering. 2021, Vol. 11 Issue 2, p184-198. 15p.

Témata: *TRAFFIC flow, *SUPERVISED learning, *PYTHON programming language, *BIG data, *STANDARD deviations, *REGRESSION trees

Geografický termín: SERBIA