National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Software demo of unsupervised learning
Slezák, Milan ; Sáblík, Václav (referee) ; Honzík, Petr (advisor)
The bachelor's thesis introduces the use of unsupervised learning and presents possibilities of cluster analysis. Software demo of unsupervised learning is a part of this thesis. This program was made as a teaching aid. It consists several input databases with different data distributions on the basis of which it is possible to explain very easily elementary principles of cluster analysis and differences between hierarchical clustering and partitional clustering.
Difference of biomechanical parameters in individual categories in javelin throw
Krejnusová, Tereza ; Feher, Jan (advisor) ; Hojka, Vladimír (referee)
Title: Difference of biomechanical parameters in individual categories in javelin throw Objectives: The aim of this work is to determine whether the biomechanical parameters in javelin throw are different between age categories and gender categories. At the same time, this work deals with how much influence the individual parameters affect the throw distance and whether these ratios are the same or different for each category. Methods: During the research, kinematic analysis and video analysis using the Kinovea program were used. Statistical methods such as ANOVA, Tukey's post hoc analysis and hierarchical regression analysis were also used. Results: It was found that of the measured parameters, the value of 8 parameters differs between at least two categories. Only 2 parameters gave an insignificant result, so there are no different values between the categories. Furthermore, it was found that for 3 categories, the net distance has the greatest effect on the rate of estimation. The other selected parameters are only partially identical and there are some differences between the categories.. Keywords: javelin throw, biomechanical parameters, difference, category, ANOVA, hierarchical analysis
Software demo of unsupervised learning
Slezák, Milan ; Sáblík, Václav (referee) ; Honzík, Petr (advisor)
The bachelor's thesis introduces the use of unsupervised learning and presents possibilities of cluster analysis. Software demo of unsupervised learning is a part of this thesis. This program was made as a teaching aid. It consists several input databases with different data distributions on the basis of which it is possible to explain very easily elementary principles of cluster analysis and differences between hierarchical clustering and partitional clustering.

Interested in being notified about new results for this query?
Subscribe to the RSS feed.