House Price Prediction Using Machine Learning
G. Naga Satish1, Ch. V. Raghavendran2, M.D. Sugnana Rao3, Ch. Srinivasulu4
1Dr. G. Naga Satish, Associate Professor, CSE Dept, BVRIT HYDERABAD.
2Dr. Ch. V. Raghavendran, Professor, IT Dept, ACET, Surampalem
3Mr. M.D. Sugnana Rao, Assistant Professor, CSE Dept, BVRIT HYDERABAD.
4Dr. Ch. Srinivasulu, Professor, CSE Dept, BVRIT HYDERABAD.
Manuscript received on 01 July 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 717-722 | Volume-8 Issue-9, July 2019 | Retrieval Number: I7849078919/19©BEIESP | DOI: 10.35940/ijitee.I7849.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Machine learning plays a major role from past years in image detection, spam reorganization, normal speech command, product recommendation and medical diagnosis. Present machine learning algorithm helps us in enhancing security alerts, ensuring public safety and improve medical enhancements. Machine learning system also provides better customer service and safer automobile systems. In the present paper we discuss about the prediction of future housing prices that is generated by machine learning algorithm. For the selection of prediction methods we compare and explore various prediction methods. We utilize lasso regression as our model because of its adaptable and probabilistic methodology on model selection. Our result exhibit that our approach of the issue need to be successful, and has the ability to process predictions that would be comparative with other house cost prediction models. More over on other hand housing value indices, the advancement of a housing cost prediction that tend to the advancement of real estate policies schemes. This study utilizes machine learning algorithms as a research method that develops housing price prediction models. We create a housing cost prediction model In view of machine learning algorithm models for example, XGBoost, lasso regression and neural system on look at their order precision execution. We in that point recommend a housing cost prediction model to support a house vender or a real estate agent for better information based on the valuation of house. Those examinations exhibit that lasso regression algorithm, in view of accuracy, reliably outperforms alternate models in the execution of housing cost prediction.
Index Terms: Machine Learning Algorithm, Lasso regression Process and Neural System, Hosing Cost Prediction.
Scope of the Article: Machine Learning