Data Science Asked by Melly Donald on February 24, 2021
I have a data set of house prices and their corresponding features (rooms, meter squared, etc). An additional feature is the sold date of the house. The aim is to create a model that can estimate the price of a house as if it was sold today. For example a house with a specific set of features (5 rooms, 100 meters squared) and today’s date (28-1-2020), what would it sell for? Time is an important component, because prices increase (inflate over time). I am struggling to find a way to incorporate the sold date as a feature in the gradient boosting model.
I think there are a number of approaches:
What are your thoughts on these two options? Are there any alternative methods?
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