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A neutral zone classifier for three classes with an application to text mining.

  • Published In: Statistical Analysis & Data Mining, 2023, v. 16, n. 6. P. 560 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Friel, Dylan C.; Li, Yunzhe; Ellis, Benjamin; Jeske, Daniel R.; Lee, Herbert K. H.; Kass, Philip H. 3 of 3

Abstract

A classifier may be limited by its conditional misclassification rates more than its overall misclassification rate. In the case that one or more of the conditional misclassification rates are high, a neutral zone may be introduced to decrease and possibly balance the misclassification rates. In this paper, a neutral zone is incorporated into a three‐class classifier with its region determined by controlling conditional misclassification rates. The neutral zone classifier is illustrated with a text mining application that classifies written comments associated with student evaluations of teaching. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Statistical Analysis & Data Mining. 2023/12, Vol. 16, Issue 6, p560
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2023
  • ISSN:1932-1864
  • DOI:10.1002/sam.11639
  • Accession Number:173368874
  • Copyright Statement:Copyright of Statistical Analysis & Data Mining is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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