Thesis Details
Metody dolování z časových řad
This thesis is focused on the field of knowledge discovery from data, specifically from time series. Main objective is to research Python programming language support in this area and then design and implement an application that will allow to demonstrate and compare selected methods. Methods are demonstrated in experiments using appropriate data set. The output of the thesis is a comparison of methods for specific tasks and the application implementing selected methods.
knowledge discovery from databases, data mining, data analysis, data visualization, time series, decomposition, representation, segmentation, annotation, summarization, forecasting, classification, clustering, search, Python programming language, cryptocurrencies
Bidlo Michal, doc. Ing., Ph.D. (DCSY FIT BUT), člen
Janoušek Vladimír, doc. Ing., Ph.D. (DITS FIT BUT), člen
Kanich Ondřej, Ing., Ph.D. (DITS FIT BUT), člen
Peringer Petr, Dr. Ing. (DITS FIT BUT), člen
Smrž Pavel, doc. RNDr., Ph.D. (DCGM FIT BUT), člen
@mastersthesis{FITMT24879, author = "Peter Krut\'{y}", type = "Master's thesis", title = "Metody dolov\'{a}n\'{i} z \v{c}asov\'{y}ch \v{r}ad", school = "Brno University of Technology, Faculty of Information Technology", year = 2022, location = "Brno, CZ", language = "slovak", url = "https://www.fit.vut.cz/study/thesis/24879/" }