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| Developing Artificial Neural Network for Predicting Mobile Phone Price Range |
Ibrahim M. Nasser, Mohammed O. Al-Shawwa, Samy S. Abu-Naser
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Abstract:
Abstract: 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.
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