Predictive model based on decision tree combined multiple regressions

Jing Rong Chen, Yu Heng Lin, Yih Guang Leu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Citations (Scopus)

Abstract

This paper combines a decision tree with multiple linear regressions to build a predictive model. The decision tree of the predictive model generates classification outputs, and the predictive model integrates linear multiple regressions into the decision tree to achieve numerical outputs. The temperature with seven days ahead is forecasted by using the predictive model. In order to demonstrate the effectiveness of the predictive model, we compare the predictive model with some different time series methods.

Original languageEnglish
Title of host publicationICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
EditorsLiang Zhao, Lipo Wang, Guoyong Cai, Kenli Li, Yong Liu, Guoqing Xiao
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1855-1858
Number of pages4
ISBN (Electronic)9781538621653
DOIs
Publication statusPublished - 2018 Jun 21
Event13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017 - Guilin, Guangxi, China
Duration: 2017 Jul 292017 Jul 31

Publication series

NameICNC-FSKD 2017 - 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery

Other

Other13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2017
Country/TerritoryChina
CityGuilin, Guangxi
Period2017/07/292017/07/31

Keywords

  • Decision tree
  • multiple linear regression
  • predictive model

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Information Systems
  • Information Systems and Management
  • Logic
  • Modelling and Simulation
  • Statistics and Probability

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