vijayaragavansk/miami_house_price_prediction

Miami house price prediction

House price forecasting is an important topic of real estate. A common misconception among people is that house prices always increase(which is not always true), because sometimes house prices reduce due to some political uncertainity or a global pandemic, builders make use of this misconception and prices above the actual market rate. So,to maintain the transparency among customers and also to make comparison easier we make use of the data driven approach. If customer finds the price of house at some given website higher than the price predicted by the model, he can reject that house.

Data driven approach (aka-Machine learning approach): House prices always tends to fluctuate, it never keeps on increasing or decreasing. A good data-driven system for predicting House price can improve the transparency among customers and increase the sales as well. This is where Machine Learning comes into picture. Machine Learning helps in predicting the House price which are quite accurate.

The project involves analysis of the house price(Dataset downloaded from kaggle) with proper data processing. Then, different models were trained and predictions are made with different algorithms like LinearRegression, Decision Tree Regressor, Random Forest Regressor, Bagging Regressor, CatBoostRegressor, Light GBM regressor etc

• Problem type - Regression
• Final Choosen Algorithm - CatBoostRegressor
• Accuracy range - 46.96% to 82.83%