|
|
Dependence Measures
Janda, Radek ; Fusek, Michal (referee) ; Michálek, Jaroslav (advisor)
This thesis focuses on characteristics of the dependence measures among random quantities, as well as its use in industry. The theoretical part focuses on examples of the characteristics used. Furthermore, the software Statistica is described here, for its possibilities of implementing such characteristics. On simple examples, the use of dependence measures is shown. In the practical part, the thesis focuses on statistical analysis of real industrial data, whilst implementing the theory mentioned above.
|
|
|
Dependence Measures
Janda, Radek ; Fusek, Michal (referee) ; Michálek, Jaroslav (advisor)
This thesis focuses on characteristics of the dependence measures among random quantities, as well as its use in industry. The theoretical part focuses on examples of the characteristics used. Furthermore, the software Statistica is described here, for its possibilities of implementing such characteristics. On simple examples, the use of dependence measures is shown. In the practical part, the thesis focuses on statistical analysis of real industrial data, whilst implementing the theory mentioned above.
|
|
|
Classical and recent approaches in cluster analysis
Řezanková, Hana
The paper focuses on the development of selected approaches in cluster analysis. There are recently proposed similarity measures for objects characterized by nominal variables, development of algorithms for k-clustering and development of methods for clustering large data files and categorical data. As concerns algorithms for k-clustering, attention is paid to take into account the uncertainty in classifying objects into clusters, namely FCM (fuzzy k-means), PCM, FPCM, RCM, RFCM and RFPCM algorithms. For large data files, algorithms CURE, ROCK, CLARA, CLARANS and BIRCH are included, for categorical data clustering there are COOLCAT and ROCK algorithms. Two-step cluster analysis to cluster large data sets with variables of different types is mentioned.
|
guest ::
