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 …

The classical fuzzy system model method kindly assumed data which is generated from
single task. This data can be acquired from the perspective of multiple task the modeling has
on intrinsic inconsistency. In this project, a multiple fuzzy system modeling method by mining
interact common hidden structure is propose to overcome the weakness of classical TSK-
based fuzzy modeling method system for multitask learning. When the classical fuzzy
modeling method are applied to multitask datasets, they usually focus on the task …