Suchergebnisse - (( (stat OR statu) python code analysis ) OR ( stateeeeeeeeeeen 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

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

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

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

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

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

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

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

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

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

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)

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

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

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

Evolutionary Insights from Sequence Analysis of Interleukin 17A (IL17A).

Autoren: Santos JC; Department of Biological Sciences, College of Liberal Arts and Sciences, St. John's University, Jamaica, Queens, NY, USA. santosj@stjohns.edu.

Quelle: Methods in molecular biology (Clifton, N.J.) [Methods Mol Biol] 2026; Vol. 2983, pp. 397-447.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Humana Press Country of Publication: United States NLM ID: 9214969 Publication Model: Print Cited Medium: Internet ISSN: 1940-6029 (Electronic) Linking ISSN: 10643745 NLM ISO Abbreviation: Methods Mol Biol Subsets: MEDLINE

MeSH-Schlagworte: Interleukin-17*/genetics , Sequence Analysis, DNA*/methods , Computational Biology*/methods , Evolution, Molecular*, Phylogeny ; Humans ; Software ; Sequence Alignment

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