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IJSTR >> Volume 9 - Issue 4, April 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Applied Research On House Price Prediction Using Diverse Machine Learning Techniques

[Full Text]



Maharshi Modi, Ayush Sharma, Dr. P. Madhavan



House Price Prediction, Real Estate, Ensemble learning, Extra Tree, Support Vector Machine, Stochastic Gradient Descent, Naïve Bayes, K Nearest Neighbor, Logistic Regression, Classification.



With the booming civilization and ever-changing market requirements, it is essential to know the market drifts. Today prediction of house prices according to the trends is the principal essence of the study. It is imperative for an individual to understand the business trends so that he can prepare his budgetary needs according to his requirements. Real Estate is an ever-growing enterprise with an expanding society. For an investor, it is essential to comprehend the business drifts, which can assist him to underwrite in the right way and augment his business throughput. Sometimes clients get dupe by the hoax market rate set up the agent due to which the real estate industry is less translucent these days. With an uptick in convince of the dataset, it's viable for a researcher to develop a model with high accuracy. The previous model with decreased accuracy and overfitting of data reduces the efficiency, whereas the proposed system resolves such issues and provides a better and enhanced model with a rich user interface. The foremost intention of this design is to develop a comprehensive model that is advantageous for a business society as well as an individual, which is the main nub of this investigation. This design is intended to assist a client by diminishing his fieldwork moreover extricate his time and money. Models are enlightened in diverse machine learning algorithms such as Extra Tree, Support Vector Machine, K Nearest Neighbor, Naive Bayes, Logistic Regression, Stochastic Gradient Descent, and they are coupled by implementing the stacking technique.



[1] Ms. Ankita Gupta, Yashwant Jangid, Tushar Tiwari, Saurabh Jain, Rushab Sawant “A Multi Feature-Based Housing Price Prediction for Indian Market Using Machine Learning”, ISSN 2347 – 8527, IJCMS December 2017
[2] William M. Doerner, Alexander N. Bogin, “Property Renovations and Their Impact on House Price Index Construction”,https://www.fhfa.gov/PolicyProgramsResearch/Research/PaperDocuments/wp1702.pdf
[3] KANG Ling-Wei and D. X. Zhu, “The Land Prices and Housing Prices —— Empirical Research Based on Panel Data of 11 Provinces and Municipalities in Eastern China”, 2013 International Conference on Management Science & Engineering (20th) July 17-19, 2013.
[4] Susmita Ray, “A Quick Review of Machine Learning Algorithms, ”. International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, India, 2019
[5] Suchibrota Dutta, Debanjan Banerjee, “Predicting the Housing Price Direction using Machine Learning Techniques”, 2017 IEEE ICPCSI
[6] Rohini Nair, Abhijit Sarma, Sagar Doshi, Ayush Varma, “House Price Prediction Using Machine Learning And Neural Networks”, 2018 Inventive Communication and Computational Technologies
[7] Zengxiang L., Mong G., Sifei L., Xulei Y., Zheng Q., Rick S., “A Hybrid Regression Technique for House Prices Prediction”, IEEE IEEM International Conference(2017)DOI: 10.1109/IEEM.2017.8289904
[8] Yajuan Tang, Pengcheng G., Shuang Qiu, “Predicting Housing Price Based on Ensemble Learning Algorithm”, IEEE IDAP (2018) DOI: 10.1109/IDAP.2018.8620781.
[9] Wei Xu, Cheng Cheng, Jiajia Wang, “A Comparison of Ensemble Methods in Financial Market Prediction”, IJCCSO 2012 International Joint Conference on Computational Sciences and Optimization
[10] Supriya Mandhare, Snehal Kathale, Chanda Chouhan, “Industrial Revolution and Artificial Intelligent”, International Journal of Engineering Research & Technology ISSN: 2278-0181 ICIATE – 2017
[11] LiLi ,Kai-HsuanChu, “Prediction of Real Estate Price Variation Based on Economic Parameters”, Proceedings of (2017) IEEE-ICASI 2017, DOI: 10.1109/ICASI.2017.7988353