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Intro to Geospatial Machine Learning, Part 2
4.1 On the spatial process of home prices
Recall the three components of the hedonic home price model - internal characteristics, like the number of bedrooms; neighborhood amenities/public services, like crime exposure; and the underlying spatial process of prices. Modeling the first two in the previous chapter still left nearly one third of the variation in price unexplained.
In this chapter, the spatial process is added, and we learn why generalizability across space is so important for geospatial machine learning. Let's start with the relevant spatial process in home prices.
To me, the most interesting housing market dynamic is that a systematic spatial pattern ...
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