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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]

 

AUTHOR(S)

Maharshi Modi, Ayush Sharma, Dr. P. Madhavan

 

KEYWORDS

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

 

ABSTRACT

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.

 

REFERENCES

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