Classification

Manas A. Pathak ()

Chapter 7 in Beginning Data Science with R, 2014, pp 115-136 from Springer

Abstract: Abstract In this chapter we look at creating classification models with R. Along with regression, classification is an important modeling technique in the data science toolset. Instead of predicting a numeric value as we did in regression, we fit a classification model to classify data points into multiple categories or classes.

Keywords: Test Data Points; Package E1071; Naive Bayes (NB); Predicted Class Label; Logistic Regression Classification Model (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-12066-9_7

Ordering information: This item can be ordered from
http://www.springer.com/9783319120669

DOI: 10.1007/978-3-319-12066-9_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().