House Price Forecasting Using Ml and RPA

Abstract

In today’s world, every individual wish for a house that suits their lifestyle and provides amenities according to their needs and budget. On today’s world prices of houses are keep on changing very frequently which proves that house prices are often overstated. There are various factors that must be taken into deliberation for predicting house prices such as number of rooms, carpet area, and other basic local amenities. By using XGBoost, Light GBM and CatBoost Boosting algorithm to predict house prices based on real-time data which is extracted using Robotic Process Automation. Automate the tasks of data extraction can be done by Robotic Process Automation. The data generated by RPA is inconsistent, hence data is get cleaned and made consistent before feeding to appropriate Machine Learning model. After data cleaning process model is created and accuracy is get achieved [1].