Suchergebnisse - (( (statu OR stat) python code analysis ) OR ( stateeeeeeeeeeeeen python code analysis ))~

Yusuf Suresinin Anlam İlişkileri ve Hikâye Birleşenlerinin Pyhton Kodlu Matematiksel Görselleştirmelerle Tahlili. (Turkish)

Alternate Title: Analysis of the Meaning Relations and Story Components of Surah Yusuf Via Python Coded Mathematical Visualizations. (English)

Autoren: Yücel, Doğan Er, Ülkü Aysel, Metin et al.

Quelle: International Journal of Social Sciences (IJSS) / Uluslararası Sosyal Bilimler Dergisi; 2025, Vol. 9 Issue 41, p1-42, 42p

Schlagwörter: TIME series analysis, THEMATIC maps, GRAPH theory, PYTHON programming language, QUR'ANIC criticism

GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Libraries.

Autoren: Fachada, Nuno Fernandes, Daniel Fernandes, Carlos M. et al.

Quelle: Future Internet; Sep2025, Vol. 17 Issue 9, p412, 28p

Schlagwörter: LANGUAGE models, EXPERIMENTAL design, PYTHON programming language, GENERATIVE pre-trained transformers, QUANTITATIVE research, BENCHMARK problems (Computer science), CODE generators

CLM App: Interlamellar Distance of Pearlite via CLM Revisited and Automated.

Autoren: Zouhar, Martin Mikmeková, Šárka Hovjacký, Jan et al.

Quelle: Materials (1996-1944); Feb2026, Vol. 19 Issue 3, p635, 17p

Schlagwörter: AUTOMATION, IMAGE analysis, QUALITY control, MICROSTRUCTURE

A statistical approach to automated analysis of the low‐contrast object detectability test for the large ACR MRI phantom.

Autoren: Golestani, Ali M. Gee, Julia M.

Quelle: Journal of Applied Clinical Medical Physics; Jul2025, Vol. 26 Issue 7, p1-9, 9p

Schlagwörter: LINEAR statistical models, IMAGING phantoms, QUALITY control, PYTHON programming language, MAGNETIC resonance imaging

Insights and Analysis of Open-source License Violation Risks in LLMs Generated Code.

Autoren: Yibo Wang Ying Wang Yue Yu et al.

Quelle: International Journal of Software & Informatics; 2025, Vol. 15 Issue 2, p145-173, 29p

Schlagwörter: OPEN source software, COPYRIGHT infringement, LANGUAGE models, DATA analytics, CODE generators, INTELLECTUAL property infringement, DETECTION algorithms

An Empirical Evaluation of Ensemble Models for Python Code Smell Detection.

Autoren: Rao, Rajwant Singh Dewangan, Seema Mishra, Alok

Quelle: Applied Sciences (2076-3417); Jul2025, Vol. 15 Issue 13, p7472, 27p

Schlagwörter: ENSEMBLE learning, FEATURE selection, BOOSTING algorithms, PYTHON programming language, COMPUTER software quality control, DESIGN failures, DATA augmentation

Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial: Introduction to computational causal inference using reproducible Stata, R, and Python code: a tutorial

Autoren: Matthew J. Smith Mohammad A. Mansournia Camille Maringe et al.

Weitere Verfasser: Matthew J. Smith Mohammad A. Mansournia Camille Maringe et al.

Quelle: Stat Med
RISalud-ANDALUCIA. Repositorio Institucional de Salud de Andalucía
instname

Schlagwörter: regression adjustment, 01 natural sciences, Article, Applications of statistics to biology and medical sciences, meta analysis, Modelos estadísticos, double-robust methods, Humans, Computer Simulation, causal inference, 0101 mathematics, Propensity Score, propensity score, Probability, Simulación por computador, Proyectos de investigación, Models, Statistical, g-formula, Causalidad, Humanos, 3. Good health, Causality, machine learning, Puntaje de propensión, G-methods, Research Design, targeted maximum likelihood estimation, Probabilidad, inverse probability weighting

Dateibeschreibung: application/pdf; application/xml

Zugangs-URL: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.9234
https://pubmed.ncbi.nlm.nih.gov/34713468
http://hdl.handle.net/10668/22539
https://hdl.handle.net/10668/24648
https://researchonline.lshtm.ac.uk/id/eprint/4664004/1/sim.9234.pdf

Shedding Light on the Black Box: Integrating Prediction Models and Explainability Using Explainable Machine Learning.

Autoren: Zhang, Yucheng Zheng, Yuyan Wang, Dan et al.

Quelle: Organizational Research Methods; Apr2026, Vol. 29 Issue 2, p202-237, 36p

Schlagwörter: PREDICTION models, MACHINE learning, ORGANIZATIONAL research, STATISTICAL models, PYTHON programming language

Python Programming: Numerical Analysis/Machine Learning Series.

Autoren: Doskas, Constantinos

Quelle: ISSA Journal; Oct2023, Vol. 21 Issue 10, p34-38, 5p

Schlagwörter: PYTHON programming language, NUMERICAL analysis, MACHINE learning

Reviewing seas of data: Integrating image‐based bio‐logging and artificial intelligence to enhance marine conservation.

Autoren: Chimienti, Marianna Kato, Akiko Seydi, Vahid et al.

Quelle: Methods in Ecology & Evolution; Feb2026, Vol. 17 Issue 2, p272-290, 19p

Schlagwörter: ARTIFICIAL intelligence, COMPUTER vision, ANIMAL tagging, ENVIRONMENTAL sciences, COOPERATION, IMAGE processing, MARINE resources conservation, DATA integration

Programmed differently? Testing for gender differences in Python programming style and quality on GitHub.

Autoren: Brooke, Siân

Quelle: Journal of Computer-Mediated Communication; Jan2024, Vol. 29 Issue 1, p1-13, 13p

Schlagwörter: PYTHON programming language, PYTHONS, RANDOM forest algorithms, GENDER

CHATGPT VS THE REST.

Autoren: Rawlinson, Nik

Quelle: APC (Future Publishing Ltd.); Mar2026, Issue 556, p60-77, 17p, 31 Color Photographs, 3 Charts

Schlagwörter: CHATGPT, ARTIFICIAL intelligence, BUSINESS writing, CODE generators

Distinguishing LLM-Generated from Human-Written Code by Contrastive Learning.

Autoren: Xu, Xiaodan Ni, Chao Guo, Xinrong et al.

Quelle: ACM Transactions on Software Engineering & Methodology; May2025, Vol. 34 Issue 4, p1-31, 31p

Schlagwörter: CHATGPT, LANGUAGE models, CODE generators, MACHINE learning

CQLLM: A Framework for Generating CodeQL Security Vulnerability Detection Code Based on Large Language Model.

Autoren: Wang, Le Chen, Chan Zhu, Junyi et al.

Quelle: Applied Sciences (2076-3417); Jan2026, Vol. 16 Issue 1, p517, 17p

Schlagwörter: COMPUTER security vulnerabilities, LANGUAGE models, COMPUTER software correctness, SOFTWARE frameworks, PENETRATION testing (Computer security), CODE generators

Explainable Machine Learning for Functional Data.

Autoren: GOODE, KATHERINE TUCKER, J. DEREK RIES, DANIEL et al.

Quelle: Journal of Data Science; Jan2026, Vol. 24 Issue 1, p125-145, 21p

Schlagwörter: SUPERVISED learning, MACHINE learning, FUNCTIONAL analysis, FEATURE extraction, FORENSIC sciences

Regularized Maximum Likelihood Estimation for the Random Coefficients Model in Python.

Autoren: Dunker, Fabian Mendoza, Emil Reale, Marco

Quelle: Mathematics (2227-7390); Dec2025, Vol. 13 Issue 23, p3764, 29p

Schlagwörter: PYTHON programming language, MAXIMUM likelihood statistics, CONSUMPTION (Economics), MATHEMATICAL programming, MULTILEVEL models, SCIENTIFIC computing

Automating fuzz driver generation for deep learning libraries with large language models.

Autoren: Zheng, Tianming Meng, Fanchao Yi, Ping et al.

Quelle: Cybersecurity (2523-3246); 1/4/2026, Vol. 9 Issue 1, p1-21, 21p

Schlagwörter: LANGUAGE models, COMPUTER software testing, TEST systems, STATISTICAL reliability, MECHANIZATION

A Firm's Operational Risk: Data Set and Empirical Evidence.

Autoren: Astvansh, Vivek Simpson, Joseph J.

Quelle: Manufacturing & Service Operations Management (M&SOM) (INFORMS); Jan/Feb2026, Vol. 28 Issue 1, p326-341, 16p

Schlagwörter: OPERATIONAL risk, TRANSFORMER models, STAKEHOLDER theory, LEGAL liability, FINANCIAL disclosure, EMPIRICAL research, NUMERICAL analysis

Geografische Kategorien: UNITED States

JDroid: Android malware detection using hybrid opcode feature vector.

Autoren: Arslan, Recep Sinan

Quelle: PeerJ Computer Science; Jul2025, p1-30, 30p

Schlagwörter: MALWARE, MACHINE learning, DATA analytics, INFORMATION technology security, ENSEMBLE learning

Reviews & Products: ANDROID (Operating system)

Quantification of racial and ethnic disparities in alcohol-related problems in light of different methodological approaches.

Autoren: Ye Y Lui CK Martinez P et al.

Quelle: Addiction (Abingdon, England) [Addiction] 2025 May; Vol. 120 (5), pp. 873-883. Date of Electronic Publication: 2025 Jan 12.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 9304118 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1360-0443 (Electronic) Linking ISSN: 09652140 NLM ISO Abbreviation: Addiction Subsets: MEDLINE

MeSH-Schlagworte: Alcohol Drinking*/ethnology , Alcohol Drinking*/epidemiology , Alcohol-Related Disorders*/ethnology , Alcohol-Related Disorders*/epidemiology , Alcoholism*/ethnology , Alcoholism*/epidemiology , Ethnicity*/statistics & numerical data , Health Status Disparities*, Black or African American/statistics & numerical data ; Hispanic or Latino/statistics & numerical data ; United States/epidemiology ; White/statistics & numerical data ; Adolescent ; Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Young Adult ; Cross-Sectional Studies