Christian Moewes

Learn More
OBJECTIVE To characterize brain functional connectivity in subjects with prechiasmatic visual system damage and relate functional connectivity features to extent of vision loss. METHODS In this case-control study, resting-state, eyes-closed EEG activity was recorded in patients with partial optic nerve damage (n = 15) and uninjured controls (n = 13). We(More)
In this paper we reason about the usefulness of two recent trends in fuzzy methods in machine learning. That is, we discuss both fuzzy support vector machines (FSVMs) and the extraction of fuzzy rules from SVMs. First, we show that an FSVM is identical to a special type of SVM. Second, we categorize and analyze existing approaches to obtain fuzzy rules from(More)
Dynamic graphs are ubiquitous in real world applications. They can be found, e.g. in biology, neuroscience, computer science, medicine, social networks, the World Wide Web. There is a great necessity and interest in analyzing these dynamic graphs efficiently. Typically, analysis methods from classical data mining and network theory have been studied(More)
In neuroscience it became popular to represent neuroimaging data from the human brain as networks. The edges of these (weighted) graphs represent a spatio-temporal similarity between paired data channels. The temporal series of graphs is commonly averaged to a weighted graph of which edge weights are eventually thresholded. Graph measures are then applied(More)
We present an approach to learn fuzzy binary decision rules from ordinal temporal data where the task is to classify every instance at each point in time. We assume that one class is preferred to the other, e.g. the undesirable class must not be misclassified. Hence it is appealing to use the Variable Consistency Dominance-based Rough Set Approach (VC-DRSA)(More)
In diesem Aufsatz geht es um die Problematik, von Experten entworfene Versuche realen Beobachtungen anzunähern. Dazu wird dieses Problem in zwei kleinere Teilprobleme zerlegt: 1.) die Suche von wiederkehrenden Mustern in temporalen Sequenzen, sogenannten Motiven, die es gilt sowohl in den Versuchen als auch in der Realität zu entdecken, und 2.) das Zuordnen(More)
In this paper we introduce a preprocessing method for safety-related applications. Since we concentrate on scenarios with highly unbalanced misclassification costs, we briefly discuss a variation of multiple-instance learning (MIL) and recall soft margin hyperplane classifiers; in particular the principle of a support vector machine (SVM). According to this(More)
Designing and assembling automobiles is a complex task which has to be accomplished in ever shorter cycles. However, customers have increasing desires w. r. t. reliability, durability and comfort. In order to cope with these conflicting constraints it is indispensable to employ tools that greatly simplify the analysis of data that is collected during all(More)