Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Machine Learning algorithms can act as a valuable analytical tool in design research. In this paper, we demonstrate the application of a decision tree learning algorithm for desig...
Survey coding is the task of assigning a symbolic code from a predefined set of such codes to the answer given in response to an open-ended question in a questionnaire (aka surve...
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
In a variety of applications, kernel machines such as Support Vector Machines (SVMs) have been used with great success often delivering stateof-the-art results. Using the kernel t...