Classification is one of the most frequent tasks in machine learning. However, the variety of
classification tasks as well as classifier methods is huge. Thus the question is coming up …

Objective The aim of this paper is to study the feasibility and the performance of some
classifier systems belonging to family of instance-based (IB) learning as second-opinion …

High throughput sequencing technology leads to a significant increase in the number of
generated protein sequences and the anchor database UniProt doubles approximately …

In the present contribution we propose two recently developed classification algorithms for
the analysis of mass-spectrometric data—the supervised neural gas and the fuzzy-labeled …

The self-organizing map (SOM) and neural gas (NG) and generalizations thereof such as
the generative topographic map constitute popular algorithms to represent data by means of …

ABSTRACT A condition in which the heart beats with an irregular or abnormal rhythm is
known as Arrhythmia. This paper presents a procedure to extract information from …

We suggest the use of alternative distance measures for similarity based classification in
Learning Vector Quantization. Divergences can be employed whenever the data consists of …

Electronic data sets are increasing rapidly with respect to both, size of the data sets and data
resolution, ie dimensionality, such that adequate data inspection and data visualization have …

The analysis of spectral data constitutes new challenges for machine learning algorithms
due to the functional nature of the data. Special attention is paid to the metric used in the …

Metric adaptation constitutes a powerful approach to improve the performance of prototype
based classication schemes. We apply extensions of Generalized LVQ based on different …