Determining House Price Using Regression

The purpose of this article is to estimate the purchasing and sale opportunities of houses on the
market by Machine learning techniques. For financial stability, the housing sector is quite critical. People
seeking to purchase a new house appear to be more cautious in their expectations and sales tactics analyzing
historical industry patterns and pricing levels, as well as potential changes. The index of our method consists
of the price of the house and its efficiency metrics, such as the amount of renovation, the distance from the
city center, the construction programs, the height of the property, the floor and the location of the apartment
in the home, and there are several other criteria. Service includes a database that recognizes the preferences
of its clients and then integrates machine learning software. The program will enable consumers to invest in
real estate without approaching brokers. It, therefore, reduces the uncertainties inherent with the deal. The
program has a login ID and a pin. At the same time, when the user searches for an attribute, the value of the
original attribute and the value of the predicted attribute are displayed.