Webinar - Multifactorial Prediction and Deviation Analysis Using Regression/Random Forests (MuPDARF)

Webinar hosted by UQ School of Languages and Cultures in collaboration with Language Technology and Data Analysis Laboratory (LADAL)

Speaker: 

Stefan Th. Gries

Stefan has held several prestigious visiting professorships at top universities including Stanford University, the University of Colorado at Boulder, the University of Chicago, and the University of California, Davis, and the Max Planck Institute for Evolutionary Anthropology. Methodologically, he is a quantitative corpus linguist at the intersection of corpus linguistics, cognitive linguistics, and computational linguistics.

Title:

Multifactorial Prediction and Deviation Analysis Using Regression/Random Forests (MuPDARF)

Abstract:

In this talk, Stefan will give a brief and relatively practical introduction to an approach called MuPDAR(F) (for Multifactorial Prediction and Deviation Analysis using Regressions/Random Forests) that I developed (see Gries & Deshors 2014, Gries & Adelman 2014 for the first applications). The main part of the talk involves using a version of the data in Gries & Adelman (2014) to exemplify how this protocol works and how it can be done in R. Secondly, Stefan will discuss a few recent extensions proposed in Gries & Deshors (2020), which have to do with:

i) how to deal with situations with more than two linguistic choices,
(ii) how predictions are made, and
(iii) how deviations are quantified.

Finally, he will briefly comment on exploring individual variation among the target speakers (based on Gries & Wulff 2020).