Describe a real-world prediction problem using urban data for which accuracy is paramount and interpretability may...

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Advance Math

Describe a real-world prediction problem using urban data forwhich accuracy is paramount and interpretability may beless important, and for which it might be preferable to use randomforests rather than decision trees. Argue why this is the case.

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RANDOM FOREST There are tons of material in circulation explaining the concept of random forest My attempt here is to explain the concept but with a touch of simplification by juxtaposing it with a few social science scenarios Those who are new to data science can get intimidated by the technical deluge and lose interest DECISION TREE There are many advantages associated with how the decision trees operate but individually decision trees introduce many problems With these problems we rarely find a robust predictive model Some of the reasons why I say so are given below as disadvantages Disadvantages I Very unstable since a variation in the dataset can lead to a very different tree taking shape The tree is very See Answer

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