This paper describes a technique called Input Reconstruction Reliability Estimation (IRRE) for determining the response reliability of a restricted class of multi-layer perceptrons (MLPs). The technique uses a network's ability to accurately encode the input pattern in its internal representation as a measure of its reliability. The more accurately a network is able to reconstruct the input pat...

10 In the past decades Machine Learning tools have been successfully used in 11 several medical diagnostic problems. While they often significantly out12 perform expert physicians (in terms of diagnostic accuracy, sensitivity, and 13 specificity), they are mostly not being used in practice. One reason for this 14 is that it is difficult to obtain an unbiased estimation of diagnose’s reliabil15 ...

Although many approaches for architecturebased reliability estimation exist, these approaches are typically limited to certain classes or exclusively concentrate on software reliability, neglecting the influence of hardware resources, component reliability, component replica and software deployment. In this paper, a reliability estimation model based on software architecture (SA) is presented. ...

Increasing demand for automatic large area surveillance has made methods estimating direction of arrival (DOA), especially acoustic methods, an interesting topic. In these systems false alarms and faults are a disturbing factor. This paper presents a reliability criterion and a new method to diminish these errors. In very low signal-to-noise ratio conditions there are seldom any means to improv...

Although machine learning algorithms have been successfully used in many problems, and are emerging as valuable data analysis tools, their serious practical use is affected by the fact that often they cannot produce reliable and unbiased assessments of their predictions’ quality. There exist several approaches for estimating reliability or confidence for individual classifications, and many of ...