Data Set A is a Pattern Matching Problem

Jens Kohlmorgen, Klaus Robert Müller

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Several data sets have been proposed for benchmarking in time series prediction. A popular one is Data Set A from the Santa Fe Competition. This data set was the subject of analysis in many papers. In this note, it is shown that predicting the continuation of Data Set A is nothing else than a pattern matching problem. Looking at studies of this data set, it is remarkable that most of the very good forecasts of Data Set A used upsampled training data. We explain why upsampling is crucial for this data set. Finally, it is demonstrated that simple pattern matching performs as good as sophisticated prediction methods on Data Set A.

Original languageEnglish
Pages (from-to)43-47
Number of pages5
JournalNeural Processing Letters
Volume7
Issue number1
DOIs
Publication statusPublished - 1998
Externally publishedYes

Keywords

  • Benchmarking
  • Pattern matching
  • Santa Fe Competition
  • Time series prediction

ASJC Scopus subject areas

  • Software
  • Neuroscience(all)
  • Computer Networks and Communications
  • Artificial Intelligence

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