That is with() function enables us to evaluate an R expression within the function to be passed as an argument. With R with() function, we can operate on R expressions as well as the process of calling that function in a single go! We often come across situations wherein we feel the need to build customized/user-defined functions to conduct out a certain operation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis.Hello, readers! In this article, we will be having a look at two closely related yet different functions of R programming - R with() and within() function, in detail.
With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis.
This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more.ĭata mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics.
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