Classification of Mobile Price Range with Different Machine Learning Algorithms and Optimized Hyperparameters

Abstract

This paper discusses the classification of mobile phones into different price ranges using basic features of mobile. Several supervised machine learning algorithms like Logistic Regression, KNN, Naïve Bayes, Random Forest, AdaBoost, XGBoost, Gradient Boosting with different optimization techniques like Grid-Search and RandomizedSearch have been applied to get the best classification model. The most important features which influences mobile price have been extracted using feature selection methods.