Comparing the stability of different clustering results of dialect data

2Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Mucha and Haimerl (2005) proposed an algorithm to determine the stability of clusters found in hierarchical cluster analysis (HCA) and to calculate the rate of recovery by which an element can be reassigned to the same cluster in successive classifications of bootstrap samples. As proof of the concept this algorithm was applied to quantitative linguistics data. These investigations used only HCA algorithms. This paper will take a broader look at the stability of clustering results, and it will take different cluster algorithms into account; e.g. we compare the stability values of partitions from HCA with results from partitioning algorithms. To ease the comparison, the same data set - from dialect research of Northern Italy, as in Mucha and Haimerl (2005) - will be used here.

Cite

CITATION STYLE

APA

Haimerl, E., & Mucha, H. J. (2007). Comparing the stability of different clustering results of dialect data. In Studies in Classification, Data Analysis, and Knowledge Organization (pp. 619–626). Kluwer Academic Publishers. https://doi.org/10.1007/978-3-540-70981-7_71

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free