Open AccessHouse Price Prediction Using Regression
Author(s) -
Meha Ajay Kumar Shukla
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40272
Subject(s) - real estate , ambiguity , computer science , feature (linguistics) , artificial neural network , regression analysis , artificial intelligence , regression , set (abstract data type) , machine learning , econometrics , economics , statistics , finance , mathematics , linguistics , philosophy , programming language
The housing sector is the second largest employment provider after agriculture sector in India and is estimated to grow at 30% over the next decade. Housing is one of the major sectors of real estate and is well complemented by the growth of the urban and semi-urban accommodations. Ambiguity among the prices of houses makes it difficult for the buyer to select their dream house. The interest of both buyers and sellers should be satisfied so that they do not overestimate or underestimate price. Our system provides a decisive housing price prediction model to benefit a buyer and seller or a real estate agent to make a better-informed decision system on multiple features. To achieve this, various features are selected as input from feature set and various approaches can be taken such as Regression Models or ANN. Keywords: Machine Learning, Artificial Intelligence, Supervised Machine Learning, Regression, Artificial Neural Network (ANN)