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Mobile Price Class prediction using Machine Learning Techniques
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 29 |
| Year of Publication: 2018 |
| Authors: Muhammad Asim, Zafar Khan |
10.5120/ijca2018916555
|
Muhammad Asim, Zafar Khan . Mobile Price Class prediction using Machine Learning Techniques. International Journal of Computer Applications. 179, 29 ( Mar 2018), 6-11. DOI=10.5120/ijca2018916555
Abstract
To predict “If the mobile with given features will be Economical or Expensive” is the main motive of this research work. Real Dataset is collected from website www.GSMArena.com . Different feature selection algorithms are used to identify and remove less important and redundant features and have minimum computational complexity. Different classifiers are used to achieve as higher accuracy as possible. Results are compared in terms of highest accuracy achieved and minimum features selected. Conclusion is made on the base of best feature selection algorithm and best classifier for the given dataset. This work can be used in any type of marketing and business to find optimal product(with minimum cost and maximum features). Future work is suggested to extend this research and find more sophisticated solution to the given problem and more accurate tool for price estimation.
References
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