A unified, coherent treatment of current classifier ensemble methods, from fundamentals of
pattern recognition to ensemble feature selection, now in its second edition The art and …

Statistical pattern recognition is a very active area of study andresearch, which has seen
many advances in recent years. New andemerging applications-such as data mining, web …

Mutual information is a good indicator of relevance between variables, and have been used
as a measure in several feature selection algorithms. However, calculating the mutual …

Fuzzy sets were first proposed by Lotfi Zadeh in his seminal paper [366] in 1965, and ever
since have been a center of many discussions, fervently admired and condemned. Both …

A probabilistic neural network (PNN) is presented for predicting the magnitude of the largest
earthquake in a pre-defined future time period in a seismic region using eight …

Driving drowsiness is a major cause of traffic accidents worldwide and has drawn the
attention of researchers in recent decades. This paper presents an application for in-vehicle …

Protein solubility is an important thermodynamic parameter that is critical for the
characterization of a protein's function, and a key determinant for the production yield of a …

The requirement to reduce the computational cost of evaluating a point probability density
estimate when employing a Parzen window estimator is a well-known problem. This paper …

We unify f-divergences, Bregman divergences, surrogate regret bounds, proper scoring
rules, cost curves, ROC-curves and statistical information. We do this by systematically …

Ordinal classification of imbalanced data is a challenging problem that appears in many real
world applications. The challenge is to simultaneously consider the order of the classes and …