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HOUSING PRICE PREDICTION
ISSN: 2582 - 9130
Publisher: author
HOUSING PRICE PREDICTION
Indexed in
Technology and Engineering
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 3
Article Operation Score: 3
Article Articles Score: 3
Article Accessibility Score: 2
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-1802
Publisher: Krishma Publication
International Journal Address (IAA):
IAA.ZONE/2582384249130
eISSN
:
2582 - 9130
VALID
ISSN Validator
Abstract
House Price Index (HPI) is commonly used to estimate the changes in housing prices. House prices strongly depend on factors such as location, area, population, it requires other information also to predict individual housing price. There has been a large number of papers adopting machine learning approaches to predict housing prices accurately, but they rarely take into account the performance of the models. This paper will validate multiple techniques in model implementation on regression and provide a better result for housing price prediction. Keywords: Housing Price Prediction; Machine Learning; Stacked Generalization
