Estimation of Mobile Phone Prices with Machine Learning

Abstract

Smart phones are getting attractive for people day by day with different features. When buying a phone, there are lots of features to look besides the price. There is no basic way to determine a telephone price according to its characteristics. Machine learning methods help to solve such a problem with minimal errors recently. But it remains that which algorithm is best suitable to solve that kind of problem. To eliminate this burden, we have investigated different machine learning algorithm on guessing telephone prices. For this one, we have used a dataset from the Kaggle that contains phone prices and features. We have performed an analysis with 25 algorithms using twenty different attributes that are effective on phone prices. The result show that the highest value with the accuracy rate of 0.9470 performed in the SVC algorithm.