Developing Artificial Neural Network for Predicting Mobile Phone Price Range

Download Edit this record How to cite View on PhilPapers
In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the price range of a mobile phone. We used a dataset that contains mobile phones information, and there was a number of factors that influence the classification of mobile phone price. Factors as battery power, CPU clock speed, has dual sim support or not, Front Camera mega pixels, has 4G or not, has Wi-Fi or not, etc…. 20 attributes were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was developed and trained, using data set, which its title is “Mobile Price Classification” and was obtained from Kaggle online community, and it is created by Abhishek Sharma. Test data evaluation shows that the ANN model is able to correctly predict the mobile price renge with 96.31 accuracy.
(categorize this paper)
PhilPapers/Archive ID
Upload history
Archival date: 2019-03-09
View other versions
Added to PP index

Total views
103 ( #41,856 of 2,438,903 )

Recent downloads (6 months)
16 ( #37,683 of 2,438,903 )

How can I increase my downloads?

Downloads since first upload
This graph includes both downloads from PhilArchive and clicks on external links on PhilPapers.