Multitask TSK fuzzy system modeling by mining intertask common hidden structure

Yizhang Jiang, Fu Lai Korris Chung, Hisao Ishibuchi, Zhaohong Deng, Shitong Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

112 Citations (Scopus)


The classical fuzzy system modeling methods implicitly assume data generated from a single task, which is essentially not in accordance with many practical scenarios where data can be acquired from the perspective of multiple tasks. Although one can build an individual fuzzy system model for each task, the result indeed tells us that the individual modeling approach will get poor generalization ability due to ignoring the intertask hidden correlation. In order to circumvent this shortcoming, we consider a general framework for preserving the independent information among different tasks and mining hidden correlation information among all tasks in multitask fuzzy modeling. In this framework, a low-dimensional subspace (structure) is assumed to be shared among all tasks and hence be the hidden correlation information among all tasks. Under this framework, a multitask Takagi-Sugeno-Kang (TSK) fuzzy system model called MTCS-TSK-FS (TSK-FS for multiple tasks with common hidden structure), based on the classical L2-norm TSK fuzzy system, is proposed in this paper. The proposed model can not only take advantage of independent sample information from the original space for each task, but also effectively use the intertask common hidden structure among multiple tasks to enhance the generalization performance of the built fuzzy systems. Experiments on synthetic and real-world datasets demonstrate the applicability and distinctive performance of the proposed multitask fuzzy system model in multitask regression learning scenarios.
Original languageEnglish
Article number06845353
Pages (from-to)548-561
Number of pages14
JournalIEEE Transactions on Cybernetics
Issue number3
Publication statusPublished - 1 Mar 2015


  • Common hidden structure
  • fuzzy modeling
  • multitask learning
  • Takagi-Sugeno-Kang (TSK) fuzzy systems

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications
  • Electrical and Electronic Engineering


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