In any diabetic retinopathy screening program, about two-thirds of patients have no
retinopathy. However, on average, it takes a human expert about one and a half times …

Diabetic retinopathy is a complication of diabetes and early detection is essential for
effective treatment. In this paper, a novel technique for the separation of normal and …

The recent credit crisis has renewed regulatory concerns of industrial interest in credit risk
analysis. To reduce exposure to credit default, it thus becomes a crucial motive to select vital …

This research considers the problem of the No-Free-Launch-Theorem, which states that no
one machine learning algorithm performs best on all problems due to algorithms having …

Feature selection is the technique commonly used in machine learning to select a subset of
relevant features for building robust learning models. Ensemble feature relevance …

In any diabetic retinopathy screening program, about two-thirds of patients have no
retinopathy. However, on average, it takes a human expert about one and a half times …

This chapter introduces the Bayesian and the evidence frameworks to construct an
automatic relevance determination method. These techniques are described in detail …

The problem of scalable image recognition has long been a research issue in the area of
computer vision. This thesis aims to address this by providing a holistic solution in which …

Feature selection is the technique commonly used in machine learning of selecting a subset
of relevant features for building robust learning models. Ensemble feature relevance …