47 citations · 150 across the 18 of their papers we have counts for
5 papers · 1 filter
Vectorial Genetic Programming -- Optimizing Segments for Feature Extraction
Philipp Fleck, Stephan Winkler, Michael Kommenda +1
Vectorial Genetic Programming (Vec-GP) extends GP by allowing vectors as input features along regular, scalar features, using them by applying arithmetic operations component-wise…
Online Diversity Control in Symbolic Regression via a Fast Hash-based Tree Similarity Measure
Bogdan Burlacu, Michael Affenzeller, Gabriel Kronberger +1
Diversity represents an important aspect of genetic programming, being directly correlated with search performance. When considered at the genotype level, diversity often requires…
Data Mining using Unguided Symbolic Regression on a Blast Furnace Dataset
Michael Kommenda, Gabriel Kronberger, Christoph Feilmayr +1
In this paper a data mining approach for variable selection and knowledge extraction from datasets is presented. The approach is based on unguided symbolic regression (every variab…
On the Success Rate of Crossover Operators for Genetic Programming with Offspring Selection
Gabriel Kronberger, Stephan Winkler, Michael Affenzeller +2
Genetic programming is a powerful heuristic search technique that is used for a number of real world applications to solve among others regression, classification, and time-series…
Macro-Economic Time Series Modeling and Interaction Networks
Gabriel Kronberger, Stefan Fink, Michael Kommenda +1
Macro-economic models describe the dynamics of economic quantities. The estimations and forecasts produced by such models play a substantial role for financial and political decisi…