Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data

Abstract

Abstract

In this study, it compares two different types of neural networks. First is a single layer neural network and other is multiple hidden layer neural network. For just comparisons it is ensured that both uses the same activation and output functions and have the same number of nodes and parameters. The networks are trained by the gradient descent algorithm to approximate linear and quadratic functions and examine their convergence properties. Here it is predicted as to how much a customer is willing to spend at a store using linear regression and different layers: single and multiple layers of neural network. Then comparison of linear regression with a single layer of neural network and single layer with multiple layers of network has done.

Keywords: Comparisons, gradient descent algorithm, hidden layers, linear regression, neural networks

Cite this Article

Amin Deep Prakashbhai. Comparative Analysis of Neural Network and Linear Regression Applied to Black Friday Data. Current Trends in Signal Processing. 2019; 9(3): 1–4p.