Machine Learning Made Easy: A Review of "Scikit-learn" Package in Python Programming Language

Autor/inn/en	Hao, Jiangang; Ho, Tin Kam
Titel	Machine Learning Made Easy: A Review of "Scikit-learn" Package in Python Programming Language
Quelle	In: Journal of Educational and Behavioral Statistics, 44 (2019) 3, S.348-361 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1076-9986
DOI	10.3102/1076998619832248
Schlagwörter	Artificial Intelligence; Statistical Inference; Data Analysis; Programming Languages; Open Source Technology; Computer Software + Suchen Sie Ihr Suchwort? Künstliche Intelligenz; Inferential statistics; Schließende Statistik; Auswertung
Abstract	Machine learning is a popular topic in data analysis and modeling. Many different machine learning algorithms have been developed and implemented in a variety of programming languages over the past 20 years. In this article, we first provide an overview of machine learning and clarify its difference from statistical inference. Then, we review "Scikit-learn," a machine learning package in the Python programming language that is widely used in data science. The "Scikit-learn" package includes implementations of a comprehensive list of machine learning methods under unified data and modeling procedure conventions, making it a convenient toolkit for educational and behavior statisticians. (As Provided).
Anmerkungen	SAGE Publications. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01