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Devs

Github Avatar Bernd Bischl

I am professor of computational statistics at the LMU Munich. I created mlr a long time ago at the beginning of my PhD. I have worked on many different parts of mlr, mainly the internal OO system, the wrappers and tuning - although quite a few people helped to refactor the package a lot and to turn it into something much better. I have probably contributed next to nothing to the great tutorial.

Github Avatar Michel Lang

I am a postdoc at the TU Dortmund and one of the main developers of mlr. I’ve worked on many internal parts of mlr and started to implement support for survival analysis.

Github Avatar Lars Kotthoff

I am assistant professor of Computer Science at the University of Wyoming. My main contributions to mlr include support for clustering. Apart from that I’m usually fighting Travis in one way or another.

Github Avatar Jakob Richter

PhD Student in Statistics at TU Dortmund. Working on mlr since 2012. Always wanting to add some functionality, ending up revising a lot of stuff. Also involved in the development in related packages as ParamHelpers and mainly mlrMBO recently.

Github Avatar Giuseppe Casalicchio

I am a PhD student at the LMU Munich and member of the computational statistics working group. I added support for several stacking algorithms.

Github Avatar Patrick Schratz

PhD Student at Friedrich-Schiller-University Jena. Environmental modeling with a focus on spatial data handling. I implemented the possibility to use spatially disjoint subsets in cross-validation settings including the corresponding tutorial section “Handling of Spatial Data”.

Github Avatar Zachary Jones

I am a PhD student at Pennsylvania State University and a former Google Summer of Code student. I work mainly on visualization, variance estimation for predictions, and functionality for exploratory data analysis. I am the plot master.

Github Avatar Erich Studerus

I am postdoc psychologist at the University of Basel Psychiatrics Clinics. I added support for several learners and filtering methods.

Github Avatar Julia Schiffner

I am a researcher at Heinrich Heine University Düsseldorf. I work mainly on expanding and improving the tutorial, but also do nice things for mlr itself.

Github Avatar Florian Fendt

I am a Master’s student at the LMU Munich and member of the computational statistics working group. I’m helping to clean up the issue tracker in general and will be implementing time series tasks in the course of my Master’s Thesis.

Github Avatar Florian Pfisterer

Master’s Student at LMU Munich, implemented some visualizations on BenchmarkResults and hopefully some more in the future.

Github Avatar Philipp Probst

PhD Student at IBE, LMU Munich. Implemented (parts of) the multilabel classification in mlr. Currently doing benchmarks on OpenML datasets with mlr, comparing different learners and getting informations and good defaults for hyperparameters of implemented learners.

Github Avatar Janek Thomas

PhD Student at LMU Munich and member of the computational statistics working group. I’m interested in variable selection and hyperparameter tuning, especially for gradient boosting. I work on variable importance, tuning and preprocessing wrappers.

Github Avatar Bruno Hebling Vieira

MSc in Physics Applied to Medicine and Biology and BSc in Medical Physics, currently pursuing a DSc also from the University of São Paulo (USP). I’m committed to add new useful measures and learners to mlr.

Github Avatar Mason Gallo

I am a graduate student at Georgia Tech with industry experience in machine learning. I implemented hyperparameter tuning visualization, and I also work on various parts of mlr along with the tutorial.

Github Avatar Quay Au

I am a PhD student at LMU Munich and member of the computational statistics working group. I implemented several multilabel algorithms.

Julia Fried

I am studying Data Science at the LMU Munich. I’ve created the mlr cheatsheet and added use cases to the mlr tutorial.

Github Avatar Kira Engelhardt

I am a Data Science student at LMU Munich. I designed the Cheatsheet and worked on the tutorial.

Github Avatar Patrick Schratz

PhD Student at Friedrich-Schiller-University Jena. Environmental modeling with a focus on spatial data handling. I implemented the possibility to use spatially disjoint subsets in cross-validation settings including the corresponding tutorial section “Handling of Spatial Data”.