Machine learning models repeatedly outperform interpretable, parametric models like the linear regression model. The gains in performance have a price: The models operate as black boxes which are not interpretable. Fortunately, there are many methods that can make machine learning models interpretable. The R package iml provides tools for analysing ...

Currently a lot of people are talking about the new shiny package. So I got curious and built an own, more or less useful app: A drink trackerThis app can be used to track how much someone drank and therefore it is very useful for every party, especial...

When I learned about principal component analysis (PCA), I thought it would be really useful in big data analysis, but that's not true if you want to do prediction. I tried PCA in my first competition at kaggle, but it delivered bad results. This post illustrates how PCA can pollute ...