We further investigate the relationship between accuracy and interpretability during the design of fuzzy systems. Both aspects are of major importance for the control of neuromuscular blockade. After describing how these goals can be measured, a multi-objective evolutionary optimization scheme is set up. The results show that even for the best optimization runs at the accuracy side of the Paret...

In computational biology, the analysis of high-throughput data poses several issues on the reliability, reproducibility and interpretability of the results. It has been suggested that one reason for these inconsistencies may be that in complex diseases, such as cancer, multiple genes belonging to one or more physiological pathways are associated with the outcomes. Thus, a possible approach to i...

Interpretability and accuracy are two important features of fuzzy systems which are conflicting in their nature. One can be improved at the cost of the other and this situation is identified as “Interpretability-Accuracy Trade-Off”. To deal with this trade-off Multi-Objective Evolutionary Algorithms (MOEA) are frequently applied in the design of fuzzy systems. Several novel MOEA have been propo...

The prime consideration in designing sustainable language resources is to ensure that they remain interpretable for coming generations of users. In this paper we adopt a new perspective on resource creation securing the interpretability of data, using a case study of Ega, an endangered African language for which a small amount of legacy data is available. Basic steps to securing interpretabilit...

In the last century, a huge multi–disciplinary scientific endeavor is devoted to answer the historical questions in understanding the brain functions. Among the statistical methods used for this purpose, brain decoding provides a tool to predict the mental state of a human subject based on the recorded brain signal. Brain decoding is widely applied in the contexts of brain–computer interfacing,...

in this paper we turn the attention to a well developed theory of fuzzy/lin-guis-tic models that are interpretable and, moreover, can be learned from the data.we present four different situations demonstrating both interpretability as well as learning abilities of these models.

this paper considers the generation of some interpretable fuzzy rules for assigning an amino acid sequence into the appropriate protein superfamily. since the main objective of this classifier is the interpretability of rules, we have used the distribution of amino acids in the sequences of proteins as features. these features are the occurrence probabilities of six exchange groups in the seque...

Objective. This study aims to assess the impact of adaptive statistical iterative reconstruction (ASIR) on CT imaging quality, diagnostic interpretability, and radiation dose reduction for a proven CT acquisition protocol for total body trauma. Methods. 18 patients with multiple trauma (ISS ≥ 16) were examined either with a routine protocol (n = 6), 30% (n = 6), or 40% (n = 6) of iterative reco...

The independence results in arithmetic and set theory led to a proliferation of mathematical systems. One very general way to investigate the space of possible mathematical systems is under the relation of interpretability. Under this relation the space of possible mathematical systems forms an intricate hierarchy of increasingly strong systems. Large cardinal axioms provide a canonical means o...