A current focus of intense research in pattern classification is the combination of several
classifier systems, which can be built following either the same or different models and/or …

The effectiveness of the treatment of breast cancer depends on its timely detection. An early
step in the diagnosis is the cytological examination of breast material obtained directly from …

The class imbalance problem is a challenge in supervised classification, since many
classifiers are sensitive to class distribution, biasing their prediction towards the majority …

Cost-sensitive learning is an aspect of algorithm-level modifications for class imbalance.
Here, instead of using a standard error-driven evaluation (or 0–1 loss function), a …

Currently, methods of combined classification are the focus of intense research. A properly
designed group of combined classifiers exploiting knowledge gathered in a pool of …

Contrast pattern-based classifiers are an important family of both understandable and
accurate classifiers. Nevertheless, these classifiers do not achieve good performance on …

Credit scoring represents a two-classification problem. Moreover, the data imbalance of the
credit data sets, where one class contains a small number of data samples and the other …

This paper presents a novel intelligent system for the automatic visual inspection of vessels
consisting of three processing levels:(a) data acquisition: images are collected using a …

Breast cancer is the most common type of cancer among women. As early detection is
crucial for the patient's health, much attention has been paid to the development of tools for …

Many classification algorithms aim to minimize just their training error count; however, it is
often desirable to minimize a more general cost metric, where distinct instances have …