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Analýza obchodních dat využitím metod rozpoznání vzoru / Analysis of business data using methods of pattern recognition

This project explores basic methods of time series analysis and decomposition of these series using the additive model. It describes creation of classes for generating and decomposition of time series in Python. This project also guides the reader through creation of Matlab user interface which is used to generate time series and mark chosen parameters. I also go through implementation of functions for time series decomposition previously created in Python. I chose seven parameters of which I kept track. I also chose general features for representing chosen parameters as well as features which were chosen carefully for each parameter. Every time series generated by this user interface are then used to train a program, which classifies them for semantic description. After training the created model was used to predict chosen parameters of previously unknown time series.

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:220412
Date January 2015
CreatorsPrišť, Lukáš
ContributorsBurget, Radim, Atassi, Hicham
PublisherVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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