Tensor Linear Regression Using Pytorch

  • Mohamed Abdul Kader Jailani

Abstract

Tensor Linear Regression is a linear supervised kind of learning in ML. In most of the dataset , the relationship between dependent variables and independent variables are a kind of linear relation in nature .The best fitting linear function which predicts the target variable of  continuous data is the main task in linear regression. This linear regression is related to the traditional best line fitting problem and can be extended to non linear functions of higher order polynomial curves. In this paper ,tensor linear regression is built in pytorch frameworkfrom scratch and tensor linear regression model is evaluated with random sample datasets and the prediction is plotted using matplotlib module. The result indicates that the R2 value whichis close to 1, is better the model.

Published
2021-11-23
How to Cite
Mohamed Abdul Kader Jailani. (2021). Tensor Linear Regression Using Pytorch. Design Engineering, 15522-15528. Retrieved from http://thedesignengineering.com/index.php/DE/article/view/6687
Section
Articles