Predicting House Prices

Abstract

Data mining has been utilized as a part of a few domains and enterprises and the business area is one of its applications. Business world is becoming more competitive. The utilization of data mining innovation has turned into an essential piece of business improvement. Many organizations depend on the utilization of data mining systems to permit managing monstrous data and to uncover the critical and obscure connections between various components of information. This supports the decision-making process and therefore quickens the business development. A few data mining techniques are utilized by business applications, for example: classification, clustering, prediction, and association. Each of these procedures has demonstrated its impact on blooming businesses. The primary objective of this Project is to help different stakeholders in real estate market in forecasting the cost of a house with a specific end goal to bolster the choice of offering or purchasing. In this project, we will use house price data of DHA 2 Islamabad and Bahria Town Islamabad. In this project, Random forest technique is used to predict the selling price of a property. The trials of the Project rely upon a dataset that was scraped from online land classifieds.