Novel Technique for Price Prediction by Using Logistic, Linear and Decision Tree Algorithm on Deep Belief Network

1B. Lalithadevi, Kashish Dubey, Yash Trivedi and Aditya Singh Gautam


The aim is to provide a house price prediction system which helps in finding the exact price of the house based on various parameters. In today’s world, House prices keep changing day in and day out and sometimes are hyped rather than being based on valuation. Predicting housing prices with real factors is the main motive of our project. Here we aim to make our evaluations based on every basic parameter that is considered while determining the price. We use various regression techniques in this pathway, and our results are not only based on one technique rather it is the weighted mean of various techniques to give most accurate results. This approach will help us get minimum error and maximum accuracy than individual algorithms applied. The existing system involves in calculation of house prices without the necessary prediction about future market trends and price increase. Houses are very expensive sometimes which are totally not worth the price. To avoid this problem where the customers are forced in paying high amount of price we propose our system.


Linear Regression, Machine Learning, Parameters, Logical Regression, Prediction.

Paper Details
IssueIssue 5