and Knowledge-Based Systems Core Unit for Medical Statistics (2009)
Mario Drobics, János Botzheim, Klaus-peter Adlassnig
In many regression learning algorithms for fuzzy rule bases it is not possible to define the error measure to be optimized freely. A possible alternative is the usage of global optimization...
Decision Tree Learning, Inductive (2009)
In this paper we present a novel approach to datadriven fuzzy modeling which aims to create highly accurate but also easily comprehensible models. This goal is obtained by defining a flexible but...
Extracting Knowledge and Computable Models from Data- Needs, Expectations, and Experience (2008)
Thomas Natschläger, Felix Kossak, Mario Drobics
Abstract In modern industrial manufacturing, a great amount of data is gathered to monitor and analyze a given production process. Intelligent analysis of such data helps to reveal as much...
Technical Report SCCH–TR–0016 Interpretation of Self-Organizing Maps with Fuzzy Rules (2007)
Mario Drobics, Werner Winiwarter, Ulrich Bodenhofer
Abstract — Exploration of large and high-dimensional data sets is one of the main problems in data analysis. Self-organizing maps (SOMs) can be used to map large data sets to a simpler, usually...
Mining clusters and corresponding interpretable descriptions - a three-stage approach (2007)
Mario Drobics, Ulrich Bodenhofer, Werner Winiwarter
This paper presents a three-stage approach to data mining which puts special emphasis on the visualization and interpretability of the results. In the first stage, the input data is represented by a...
Mario Drobics, Ulrich Bodenhofer, Werner Winiwarter
Identifying structures in large data sets raises a number of problems. On the one hand, many methods cannot be applied to larger data sets, while, on the other hand, the results are often hard to...
Interpretation of selforganizing maps with fuzzy rules (2000)
Mario Drobics, Werner Winiwarter, Ulrich Bodenhofer
Exploration of large and high-dimensional data sets is one of the main problems in data analysis. Self-organizing maps (SOMs) can be used to map large data sets to a simpler, usually two-dimensional,...