We show that, by using a discriminate kernel machine such as a support vector machine, the approach can reveal discriminative motifs underlying the kernel ...
Like many other kernels, the WD kernel is a black-box that hinders di- rect interpretation and analysis of the classifier that is output by the kernel- based ...
A probabilistic approach to automatically extract the subsequences--or motifs--truly underlying the machine's predictions, which can discover even difficult ...
Opening the black box: Revealing interpretable sequence motifs in kernel-based learning algorithms. Marina M.C. Vidovic, Nico Görnitz, Klaus Robert Müller ...
Bibliographic details on Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms.
... Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms}}, booktitle={Machine Learning and Knowledge Discovery in ...
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms ... Sequence Motifs in Kernel-Based Learning Algorithms.
Opening the Black Box: Revealing Interpretable Sequence Motifs in Kernel-Based Learning Algorithms ... algorithmic implementation of multiclass kernel-based ...
Here, we discuss the importance of interpretable ML, different strategies for interpreting ML models, and examples of how these strategies have been applied.
Missing: Motifs | Show results with:Motifs
Opening the black box: Revealing interpretable sequence motifs in kernel-based learning algorithms. MMC Vidovic, N Görnitz, KR Müller, G Rätsch, M Kloft.