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Workshop: An Introduction to Machine Learning in R

Dr. Clemens Stachl and Dr. Florian Pargent (Psychological Methods and Assessment, Department of Psychology, Ludwig-Maximilians-Universität München)

Friday, 26th October 2018, 9 am to 5 pm

The majority of psychological research is aimed at explaining human experience and behavior with methods of inferential statistics. This is not always in line with the intention to predict psychological variables and associated outcomes with utmost precision (Yarkoni, 2017). Models and techniques from the field of machine learning were developed to achieve a maximum of predictive performance. Whereas, machine learning models have long been considered black-boxes, recent developments have greatly increased their interpretability. For these reasons, the psychological research community shows increasing interest in adopting these methods.

In this workshop, we will give a non-technical introduction to the basic concepts and ideas of machine learning. We will discuss the bias variance tradeoff, overfitting, resampling techniques, model evaluation and variable selection. Participants will be introduced to the Random Forest (Breiman, 2001), a powerful, nonlinear machine learning algorithm that is known for its high predictive performance in many application settings. To demonstrate the strengths of the Random Forest, we will compare its performance with linear regression models in a series of benchmark experiments. In addition to performance evaluation, researchers are often interested in the importance of single predictors. In this regard, variable importance measures and partial dependency plots are useful.

After this workshop, participants should be able to apply basic machine learning techniques to their own research.

Originally, the workshop was designed for psychologists but early-stage researchers from other disciplines are also invited to participate.

Previous knowledge is required:

  • Basic knowledge of the software R: Participants should be able to import data sets and be able to execute statistical analyses independently.
  • Basic statistical knowledge: Participants should be familiar with linear regression modeling Participants are also asked to bring their laptops with them.

Technical information, i. e. about which parts of the R package have to be installed, will be issued in due time before the beginning of the workshop.

The workshop will be held in English but participants are invited to ask questions or make remarks in German as well.

Friday, 26th October 2018, 9am to 5 pm

Seminar room of the graduate school
“City-Passage Lindenthal”, 2nd floor, Dürener Str. 89, D-50931 Cologne

Please register until October 15th via e-mail to: Graduiertenschule-HFSpamProtectionuni-koeln.de.