Efficient Approaches for House Pricing Prediction by Using Hybrid Machine Learning Algorithms

To own a house is dream of many. However, in this age of inflation and sky rocketing housing prices, its not always easy to find dream home within the constrained budget. Also, in addition to budget, there are several other factors that contributes towards finding the right home-location, ease of access, transportation etc. In such a scenario, a house price predicting system will be helpful for both buyers and sellers. This research aims to predict house prices in IOWA state, USA using regression analysis. The prediction is arrived at by help of various explanatory variables such as area of the property, location of the house, material used for construction, age of the property, number of bedrooms and garages and so on. This paper elaborates on the performance of Linear regression and Ridge regularization for model prediction. It also details the machine learning techniques used and its significance pertaining to the results.