Titlebook: Intelligent Information Processing and Web Mining; Proceedings of the I Mieczys?aw A. K?opotek (Conference Co-Chair),S?awo Conference proce

Coronation

Mining Spatial Association Rulesed T-tree, for storing frequent and potentially frequent itemsets has been introduced. Spatial objects are represented here as points. Non-spatial items contain information considering spatial elements. Discovered associations contain information including both spatial and non-spatial elements.

Kaleidoscope

On Admissible Substitutions in Classical and Intuitionistic Sequent Logicsmizing quantifier riles applications. This play a special role for . because using analog of skolemization for . requires sophistical technique of formulas transformation. Some results about the modifications of the calculi . and . are given. A special example illustrates the different ways of applying the notions of admissibility.

grieve

動(dòng)機(jī)

State Assignment by Evolutionary Algorithms System (MAX+PLUS II). Experimental results show that solutions found by EA are significantly better (up to 55%) than those from MAX+PLUS II, moreover EA equipped with proposed crossover operators found better results than those obtained with the use of other crossovers.

花費(fèi)

直言不諱

Exploiting sensitivity analysis in Bayesian networks for customer satisfaction study sensitivity analysis of the model’s probabilistic parameters, which enables us to classify the dimensions with respect to their (non) linear and synergy effects on low and high overall satisfaction judgments. Selected results from a real-world case study are shown to demonstrate the usefulness of the approach.

superfluous

On Learning of Sunspot Classificationisk were taken from the NASA SOHO satellite’s MDI instrument and sunspots extracted using image processing techniques. Two data mining tools, WEKA and RSES, were used for learning sunspot classification. In the training dataset sunspots were manually classified by comparing extracted sunspots with corresponding active region maps.

割公牛膨脹

hedonic

Confusion Matrix Visualizationerror is not sufficient. The approach may be used to control and tune different classifiers applied to the same data set or a single classifier applied to different data sets. The results of such analyses may then be used for identifying the combinations of classes that proved to be worst recognized.

menopause

Independent Component Analysis for Filtration in Data Miningution. Our aim is to utilize results from many models, identify common destructive components as precisely as possible and eliminate them. This will be done by Independent Component Analysis .. The modified . -algorithm for effective problem solving will be proposed.