Real Estate Price Prediction

Abstract

Real estate is one of the the unrecognized industries of the world. House prices keep changing day to day and sometimes price range is high or hyped and more than the house evaluation. Therefore, Predicting the right price and valid price of the house is the main aim of our project. Here our aim is to predict the price of the houses based on certain basic parameters like number of bathroom hall kitchen, locality etc. We have use different regression techniques to predict the prices and results are not only based on one technique. Rather we used different techniques and used the most accurate technique for the final result. The result with minimum error and maximum accuracy yields the final result. This paper uses Machine Learning algorithms to predict the prices of the houses on real dataset downloaded from Kaggle. There are very less resources on this real estate price prediction to refer.This paper gives review of the implementation of Machine Learning models and we are trying to make the model so accurate so that it can be implemented in real life. The results tells that how different algorithms can affect the accuracy of the predicted results. Also a dataset which is uneven can affect the results.The paper finally gives the algorithm which predicts the most accurate results.