Fuzzy Clustering to Study Various Regression Models with Fractional Brownian Motion Errors

EasyChair Preprint no. 7774

Abstract

Clustering numerous regression models fitted on the dataset is one of the most ubiquitous issues in different fields of sciences. This research aims to compare and to classify different regression models with fractional Brownian motion errors which can be used for a dataset. Our primary objective is to cluster these models based on fuzzy clustering and then to detect a subset of inexpensive predictors to predict a response variable reasonably well.

Keyphrases: data modeling, fractional Brownian motion, fuzzy clustering, Regression

@Booklet{EasyChair:7774,
  author = {Mohammad Reza Mahmoudi and Mohammad Hossein Heydari and Kim-Hung Pho},
  title = {Fuzzy Clustering to Study Various Regression Models with Fractional  Brownian Motion Errors},
  howpublished = {EasyChair Preprint no. 7774},

  year = {EasyChair, 2022}}