Missing value algorithms in decision trees

Hyunjoong Kim, Sumer Yates

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Seven decision tree algorithms for missing values were compared based on split point selection, split variable selection, and the predictive accuracy. The simulation experiments were carried out under two scenarios. We found that the performance of missing value algorithms depends on the characteristic of data set under the analysis and none can outperform others in all cases.

Original languageEnglish
Title of host publicationStatistical Data Mining and Knowledge Discovery
PublisherCRC Press
Pages155-172
Number of pages18
ISBN (Electronic)9780203497159
ISBN (Print)9781584883449
Publication statusPublished - 2003 Jan 1

All Science Journal Classification (ASJC) codes

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)
  • Computer Science(all)

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  • Cite this

    Kim, H., & Yates, S. (2003). Missing value algorithms in decision trees. In Statistical Data Mining and Knowledge Discovery (pp. 155-172). CRC Press.