A preliminary study of prediction interval methods with genetic programming

Karina Brotto Rebuli, Mario Giacobini, Niccolò Tallone, Leonardo Vanneschi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This article presents an exploratory study on modelling Prediction Intervals (PI) with two Genetic Programming (GP) methods. A PI is the range of values in which the real target value is expected to fall into. It should combine two contrasting properties: to be as narrow as possible and to include as many data observations as possible. One proposed GP method, called CWC-GP, evolves simultaneously the lower and upper boundaries of the PI using a single fitness measure that combines the width and the probability coverage of the PI. The other proposed GP method, called LUBE-GP, evolves independently the boundaries of the PI with a multi-objective approach, in which one fitness aims to minimise the width and the other aims to maximise the probability coverage of the PI. Both methods were applied with Direct and Sequential approaches. In the former, the PI is assessed without the crisp prediction of the model. In the latter, the method makes use of the crisp prediction to find the PI boundaries. The proposed methods showed to have good potential on assessing PIs and the presented preliminary results pave the way to further investigations. The most promising results were observed with the Sequential CWC-GP.
Original languageEnglish
Title of host publicationGECCO’22 Companion
Subtitle of host publicationProceedings of the 2022 Genetic and Evolutionary Computation Conference Companion
PublisherAssociation for Computing Machinery (ACM)
Pages530-533
Number of pages4
ISBN (Print)987-1-4503-9268-6
DOIs
Publication statusPublished - 19 Jul 2022
EventGECCO 2022 - The Genetic and Evolutionary Computation Conference - Boston, United States
Duration: 9 Jul 202213 Jul 2022
https://gecco-2022.sigevo.org/HomePage

Conference

ConferenceGECCO 2022 - The Genetic and Evolutionary Computation Conference
Abbreviated titleGECCO'22
Country/TerritoryUnited States
CityBoston
Period9/07/2213/07/22
Internet address

Keywords

  • prediction interval
  • crisp prediction
  • Modelling uncertainty

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