Vector piece-wise regression versus clustering (definition and comparative analysis)

Victor L. Brailovsky*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The problem of vector piece-wise regression is formulated. The case where the domain of definition of a vector response function consists of a number of regions of smoothness is considered. The number of the regions and their boundaries are not known and they should be found by analysing a sample of signal corrupted by noise. The solution may be obtained by combination of a dynamic programming algorithm and a probabilistic estimate. The comparison with the approach based on cluster analysis technique, is considered and some experimental results are presented.

Original languageEnglish
Pages (from-to)227-235
Number of pages9
JournalPattern Recognition Letters
Issue number4
StatePublished - Apr 1992


  • Vector piece-wise regression
  • cluster analysis
  • dynamic programming
  • probabilistic estimate


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