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Applications of R to evaluate environmental data science problems
Author(s) -
Kadiyala Akhil,
Kumar Ashok
Publication year - 2017
Publication title -
environmental progress and sustainable energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.495
H-Index - 66
eISSN - 1944-7450
pISSN - 1944-7442
DOI - 10.1002/ep.12676
Subject(s) - computer science , data science , software , exploratory data analysis , statistical software , exploratory research , software engineering , data mining , programming language , sociology , anthropology
Open source programming languages and software platforms play a vital role in the progress of research towards developing new methods for addressing data science problems. R is one such platform that the research community may adapt and make the required changes to the codes in accordance with the requisite needs, specifically when analyzing data in different forms (structured, semistructured, unstructured). This study demonstrated the applications of R for analyzing in‐bus carbon dioxide concentrations by: (i) importing the data into RStudio; (ii) performing an exploratory data analysis; (iii) developing statistical regression models; and (iv) developing tree models using machine learning methods. The readers may adopt the methods discussed in this paper to successfully address their own data science problems. © 2017 American Institute of Chemical Engineers Environ Prog, 36: 1358–1364, 2017