Python Machine Learning Blueprints - Second Edition
by Alexander Combs, Saurabh Chhajed, Michael Roman
Extending the model
At this point, we have only examined the relationship between the ZIP code, bedrooms, and rental price. And while our model had some explanatory benefit, we had a minimal dataset and far too few features to adequately examine the complex world of real estate valuation.
Fortunately, however, if we were to add more data and features to the model, we could use the exact same framework to expand our analysis.
Some possible future extensions to explore would be utilizing data for restaurants and bars available from APIs such as Foursquare or Yelp, or walkability and transportation-proximity measures from providers such as Walk Score.
There are a number of ways to extend the model, and I suggest if you do pursue working on a ...
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