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Category: Random forest

Random forest interpretation – conditional feature contributions

October 24, 2016

In two of my previous blog posts, I explained how the black box of a random forest can be opened up by tracking decision paths along the trees and computing feature contributions. This way, any prediction can be decomposed into … Continue reading →

Posted in Random forest | Replies: 25

First Estonian Machine Learning Meetup

November 24, 2015

Today, we had the first event of the Estonian Machine Learning Meetup series. I was quite baffled by the pretty massive turnout, with more than a hundred people attending, indicating that such an event series is long overdue. So props … Continue reading →

Posted in Machine learning, Random forest | Replies: 1

Random forest interpretation with scikit-learn

August 12, 2015

In one of my previous posts I discussed how random forests can be turned into a “white box”, such that each prediction is decomposed into a sum of contributions from each feature i.e. .I’ve a had quite a few requests … Continue reading →

Posted in Machine learning, Random forest | Replies: 50

Prediction intervals for Random Forests

June 2, 2015

An aspect that is important but often overlooked in applied machine learning is intervals for predictions, be it confidence or prediction intervals. For classification tasks, beginning practitioners quite often conflate probability with confidence: probability of 0.5 is taken to mean … Continue reading →

Posted in Confidence intervals, Random forest | Replies: 37

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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