Magdalena Smetek

Learn More
In the paper we presented the guidelines for the application of nonparametric statistical tests and post hoc procedures devised to perform multiple comparisons of machine learning algorithms. We emphasized it is necessary to distinguish between pairwise and multiple comparison tests. We showed that the pairwise Wilcoxon test, when employed to multiple(More)
Our recently proposed method to predict from a data stream of real estate sales transactions based on ensembles of genetic fuzzy systems was extended to include weighting component models. The method consists in incremental expanding an ensemble by models built over successive chunks of a data stream. The predicted prices of residential premises computed by(More)
A method to predict from a data stream of real estate sales transactions based on ensembles of genetic fuzzy systems was proposed. The approach consists in incremental expanding an ensemble by models built over successive chunks of a data stream. The predicted prices of residential premises computed by aged component models for current data are updated(More)
In the paper we present extensive experiments to evaluate our recently proposed method applying the ensembles of genetic fuzzy systems to build reliable predictive models from a data stream of real estate transactions. The method relies on building models over the chunks of a data stream determined by a sliding time window and incrementally expanding an(More)
The problem of model selection to compose a heterogeneous bagging ensemble was addressed in the paper. To solve the problem, three self-adapting genetic algorithms were proposed with different control parameters of mutation, crossover, and selection adjusted during the execution. The algorithms were applied to create heterogeneous ensembles comprising(More)
A method of self-adaptive mutation, crossover and selection was implemented and applied in four genetic algorithms. So developed self-adapting algorithms were then compared, with respect to convergence, with a traditional genetic one, which contained constant rates of mutation and crossover. The experiments were conducted on six benchmark functions(More)
Six variants of self-adapting genetic algorithms with varying mutation, crossover, and selection were developed. To implement self-adaptation the main part of a chromosome which comprised the solution was extended to include mutation rates, crossover rates, and/or tournament size. The solution part comprised the representation of a fuzzy system and was(More)
  • 1