Programming Collective Intelligence: Building Smart Web 2.0 Applications by Toby Segaran

Author:Toby Segaran [Segaran, Toby]
Language: eng
Format: epub, pdf
Tags: COMPUTERS / Intelligence (AI) & Semantics
ISBN: 9780596158422
Publisher: O'Reilly Media
Published: 2007-08-15T23:00:00+00:00

Figure 7-6. Decision tree for house prices

Of course, if you were only interested in guessing the price of particular property, you could just use the Zillow API to get an estimate. What’s interesting here is that you actually built a model of the factors to be considered in determining housing prices. Notice that the top of the tree is Bathrooms, which means that you reduce the variance the most by dividing the dataset on the total number of bathrooms. The main deciding factor in the price of a house in Cambridge is whether or not it has three or more bathrooms (usually this indicates that the property is a large multifamily house).

The obvious downside of using a decision tree here is that it’s necessary to create buckets of price data, since they’re all different and have to be grouped in some way to create useful endpoints. It’s possible that a different prediction technique would have worked better on the actual price data. Chapter 8 discusses a different method for making price predictions.

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