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Monthly Archives: October 2014

Interpreting random forests

October 19, 2014

Why model interpretation?Imagine a situation where a credit card company has built a fraud detection model using a random forest. The model can classify every transaction as either valid or fraudulent, based on a large number of features. What if, … Continue reading →

Posted in Machine learning, Random forest | Replies: 59

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