Or a less clickbaity title: Model based optimization of machine learning models with mlr and mlrMBO. I recently participated in the #TEFDataChallenge a datathon organized by Wayra. The first price was a drone for every team member, which is a pretty ...

Learners use hyperparameters to achieve better performance on particular datasets. When we use a machine learning package to choose the best hyperparmeters, the relationship between changing the hyperparameter and performance might not be obvious. ml...

The mlr developer team is quite international: Germany, USA, Canada. The time difference between these countries sometimes makes it hard to communicate and develop new features. The idea for this workshop or sprint was to have the possibility to talk ...

Learners use features to make predictions but how those features are used is often not apparent. mlr can estimate the dependence of a learned function on a subset of the feature space using generatePartialDependenceData. Partial dependence plots reduce the potentially high dimensional function estimated by the learner, and display a ...

There are already some benchmarking studies about different classification algorithms out there. The probably most well known and most extensive one is the Do we Need Hundreds of Classifers to Solve Real World Classication Problems? paper. They use d...