CurFi: An automated tool to find the best regression analysis model using curve fitting

Abstract

Abstract Regression analysis is a well known quantitative research method that primarily explores the relationship between one or more independent variables and a dependent variable. Conducting regression analysis manually on large datasets with multiple independent variables can be tedious. An automated system for regression analysis will be of great help for researchers as well as non‐expert users. Thus, the objective of this research is to design and develop an automated curve fitting system. As outcome, a curve fitting system named “CurFi” was developed that uses linear regression models to fit a curve to a dataset and to find out the best fit model. The system facilitates to upload a dataset, split the dataset into training set and test set, select relevant features and label from the dataset; and the system will return the best fit linear regression model after training is completed. The developed tool would be a great resource for the users having limited technical knowledge who will also be able to find the best fit regression model for a dataset using the developed “CurFi” system.

Keywords

• best fit
• curve fitting
• least squares
• machine learning
• regression
• regression analysis