Analysing the Factors Influencing the House Prices and Studying House Price Prediction Methods

Abstract

Home buyers looking for a new house tend to be very cautious with their budgets and market strategies. They
always try to optimise the budget in such a way that it matches their requirements and needs. Therefore prediction
of price becomes a very important thing when it comes to planning a budget and there is a need for a prediction
tool. This can be achieved by doing data analysis notably Exploratory Data Analysis (EDA) and by developing
Machine Learning models. An ideal home that a customer dreams of is something that matches as well as fulfils the
customer’s requirements but at the same time with an appropriate budget. So instead of going to the real estate
agent and paying an additional expense in the form of commission, the same work of suggesting and predicting
the price after analysing large data, is done by various machine learning models in a more efficient manner.
Thus the research on house price prediction is of much significance as it caters to two stakeholders in this real
estate market, home buyers will have a better understanding of property value and will be helped in the decision
making process and hence stand a better stand at negotiating. The other stakeholder i.e. the home seller will get
a better estimate to put selling cost on property.