Towards Qualitative Assessment of Machine Learning Algorithms: Utilising Signal Modality Characterisation

A novel method for the assessment of the qualitative performance of machine learning algorithms is proposed. This is achieved by a modification of the recently proposed "delay vector variance" (DVV) method for the signal modality characterisation. Based on the local predictability in phase space we propose to employ the scatter diagram of DVV features in order to gauge the changes in signal nature after being processed by machine learning algorithms. A set of comprehensive simulations on representative data sets supports the analysis.