House Price Prediction Using Machine Learning Technique
Background: House Price Prediction is an effective way to predict the price of a real estate property for the next 5 to 7 years in a particular geographical area . It helps people to make an estimate for their property in a particular location . It’s very helpful for the property dealers, property investors and various businessmen and becoming more useful for everyone day by day .
Objective: In this project we mainly deal with the house price prediction of a real estate property of a particular geographical location after 5 to 7 years. Here python and its variance used to analyse the data of the price of real estate property in that locality in the next 5 to 7 years.
Methodology: The methodology used in this research paper (house price prediction) for the upcoming next 5 to 7 years in a particular locality is the linear regression using multiple variables and Artificial Neural Network (ANN) for the accuracy in the data.
Result and Discussion: In this paper the accuracy of an algorithm that has performed for better prediction result in artificial neural network than linear regression with multiple variables. To attain the maximum accuracy in predicting the price of the house of a particular geographical locality we use artificial neural network (ANN) and the accuracy recorded of the paper 92%.
Conclusion & Future Work: Using machine learning to attain more accuracy in predicting house price and in other lines such as deep learning, data science etc.
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