Paper Title :Encompass Priceprofecy of House Using Machine Learning

Author :Rasika Sachin Golhar

Article Citation :Rasika Sachin Golhar , (2023 ) " Encompass Priceprofecy of House Using Machine Learning " , International Journal of Management and Applied Science (IJMAS) , pp. 67-70, Volume-9,Issue-4

Abstract : Encompass Price Profecy is used to evaluate the variably changing house prices. Since housing price is strongly correlated with factors such as location, area, population and inquires other information apart from to predict individual housing prices. The problem faced by customers in finding houses has been an issue of all time and is increasing due to malpractices by the builders and construction companies which tends to problem for customers only. There has been a considerably large number of papers adopting traditional machine learning approaches to predict housing prices accurately, but they are less concerned about the performance of individual models and neglect the less popular yet complex models. This model takes into consideration of the various data points and modulates itthemhrough the various machine learning algorithms like linear regression model and convolution neural networks which check the image recognition and convertsit to data and recognition of image points. The dataset developed gets validated through the regression algorithm and gives a prediction with maximum accuracy and efficiency. Keywords - Housing Price Prediction; Linear Regression; Machine Learning; Artificial Intelligence

Type : Research paper

Published : Volume-9,Issue-4

	|		PDF	|	Viewed - 34	|	Published on 2023-07-17