Convergence of Cloud with AI for Big Data Analytics

17Comparison of Various Classification Models Using Machine Learning to Predict Mobile Phones Price Range

Chinu Singla^1* and Chirag Jindal²

¹ Department of Computer Science and Engineering, Punjabi University Patiala, Punjab, India

² Department of Computer Science and Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India

Abstract

Classification is the Machine Learning technique used for classifying categorical data. In this chapter, different classification models are used to predict the price range of the different mobile phones based upon their features. The use and demand of Mobile phones seem to be at their peak today, and this trend does not seem to go down in the near future. Therefore, an efficient system needs to predict the mobile prices’ range based on its features. We have taken the mobile phone dataset containing information about their various features and functions for our research. After that, pre-processing is being performed to remove the ambiguities before applying the classification models. The Price range can be of any category between 0 and 3, where 0 represents cheapest and 3 costliest. We aim to find the classification model with the best results. Accuracy and R2 score are used to select the best model.

Keywords: Classification, mobile phones, decision tree, logistic regression, Naive Bayes, support vector machine KNN, accuracy, prediction

17.1 Introduction

Machine Learning (ML) is all about creating a machine that can ...