idalab seminar #2: “Interpretation of multivariate machine learning models and time series connectivity analyses in the presence of correlated noise”
As part of the idalab talks, on May 20th we will host Stefan Haufe, who will discuss “Interpretation of multivariate machine learning models and time series connectivity analyses in the presence of correlated noise”. The talk will start at 4:00 pm.
Besides accurate prediction/description of the data, one goal in multivariate machine learning is to gain insights into the problem domain by analyzing what aspects of the data are most relevant for the model to achieve its performance. However, such analyses may give rise to misinterpretation in the sense that data features that are for example relevant for a classification task, are not necessarily informative of any of the classes themselves.
Haufe’s talk will point out this problem and its implications in the context of linear “decoding” applications in neuroimaging, demonstrating that it is caused by correlated additive noise, and proposing a simple transformation of linear methods into a representation from which the class-specific features of actual interest can be easily read off.
Another domain in which correlated noise can lead to misinterpretation is the analysis of interactions between time series. Using again an example from neuroimaging, the talk will point out how linear mixing of noise or signal components in the data can lead to spurious detection of interaction for some of the most established interaction measures. To deal with this problem, a number of “robust” measures and demonstrate their advantages on simulated data will be introduced.
View the presentation slides on SlideShare.
Dr. Stefan Haufe is Marie Curie Postdoctoral Research
Fellow at Technische Universität Berlin
S. Haufe, F. Meinecke, K. Görgen, S. Dähne, J. Haynes, B. Blankertz, F. Bießmann, On the interpretation of weight vectors of linear models in multivariate neuroimaging
About idalab talks
We frequently invite leading scholars, data scientists, business experts and big data thought leaders to discuss their work, gain new perspectives and generate fresh insights. idalab talks are hosted on an irregular basis and are open to friends and family.