Vehicle Price Prediction using SVM Techniques
S.E.Viswapriya1, Durbaka Sai Sandeep Sharma2, Gandavarapu Sathya kiran3
1S. E. Viswapriya, Assistant Professor, Sri Chandra Sekharendra Saraswathi Viswa Maha Vidhyalaya, Kanchipuram, India.
2Durbaka Sandeep Sharma, Sri Chandra Sekharendra Saraswathi Viswa Maha Vidhyalaya, Kanchipuram, India.
3Gandavarapu Sathya Kiran, Sri Chandra Sekharendra Saraswathi Viswa Maha Vidhyalaya, Kanchipuram, India.
Manuscript received on May 14, 2020. | Revised Manuscript received on May 25, 2020. | Manuscript published on June 10, 2020. | PP: 398-401 | Volume-9 Issue-8, June 2020. | Retrieval Number: 100.1/ijitee.G5915059720 | DOI: 10.35940/ijitee.G5915.069820
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Abstract: The prediction of price for a vehicle has been more popular in research area, and it needs predominant effort and information about the experts of this particular field. The number of different attributes is measured and also it has been considerable to predict the result in more reliable and accurate. To find the price of used vehicles a well defined model has been developed with the help of three machine learning techniques such as Artificial Neural Network, Support Vector Machine and Random Forest. These techniques were used not on the individual items but for the whole group of data items. This data group has been taken from some web portal and that same has been used for the prediction. The data must be collected using web scraper that was written in PHP programming language. Distinct machine learning algorithms of varying performances had been compared to get the best result of the given data set. The final prediction model was integrated into Java application.
Keywords: Artificial neural network, Support vector machine, Random forest.
Scope of the Article: Artificial Neural Network