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Data Mining in the Field of English Football League Third Division's Betting Odds
Faruzel, Jiří ; Berka, Petr (advisor) ; Šimůnek, Milan (referee)
Thesis "Data Mining in the Field of English Football League Third Division's Betting Odds" deals with data mining referring to acquiring knowledge from data. The main objective of this work is to develop data models for prediction of match results and to compare these predictions with a chosen strategy of betting. The selected betting strategy is based on betting single bets with odds belonging to chosen intervals, which generate a profit. These odds intervals were discovered by analyzing 2006-2009 football matches in a created simulator. On the basis of these odds ranges data models were constructed. Each data model contains a hypothesis which is generated by SD4ft procedure of LispMiner based on all football matches played in seasons 2001-2008. Developed data models are tested afterwards using 2006-2009 football matches data. Results show that all derived data models are profitable in all four seasons under consideration. More than half of them successfully predicted 2009 matches as well. The analysis showed that betting agencies offer mostly odds which make it almost impossible to be profitable while betting on matches according to their odds. In spite of this fact I identified some odds intervals with which you can success while betting single bets on home-team, draw or visitor-team with odds falling within these intervals. Association rules with reasonable confidence and support can generate high profitability. It is important to realize that there are no data models which guarantee a certain profit. Most of developed data models are not applicable in the real world, some of them can actually generate a loss. Nevertheless there are data models to be found that could generate a profit in the real world.
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Systém předzpracování dat pro dobývání znalostí z databází
Kotinová, Hana ; Berka, Petr (advisor) ; Šimůnek, Milan (referee)
Abstract Aim of this diploma thesis was to create an aplication for data preprocessing. The aplication uses files in csv format and is useful for preparing data while solving datamining tasks. The aplication was created using the programing language Java. This text discusses problems, their solutions and algorithms associated with data preprocessing and discusses similar systems such as Mining Mart and SumatraTT. A complete aplication user guide is provided in the main part of this text.
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Matematické modelování spotřeby zemního plynu zákazníků bez pruběhového měření
Čermáková, J. ; Bečvář, J. ; Naxerová, O. ; Brabec, Marek ; Brabec, Tomáš ; Konár, Ondřej ; Malý, Marek ; Musílek, Petr ; Pelikán, Emil ; Šimůnek, Milan ; Vondráček, Jiří
Understanding consumption behavior of customers is essential for natural gas distribution and trading companies. For large customers, consumption is measured daily or, at least, monthly. However, meter readings are taken and consequently billed in approximately 12-month intervals in small commercial and resident sectors. This period is too long with respect to the needs of gas companies. Furthermore, the companies have to estimate unbilled revenues at the end of an accounting period. Thus, there is a strong interest in mathematical modeling of the consumption patterns as a basis of such estimates. This paper discusses requirements for unbilled revenues estimation, and summarizes experience with mathematical model GAMMA used by West Bohemian Gas Distribution Company in Pilsen, Czech Republic. In addition, plans for further development of model GAMMA are presented in connection with a research grant awarded by the Grant Agency of the Academy of Science of the Czech Republic.
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Predikce spotřeby pomocí systému ELVÍRA
Pelikán, Emil ; Šimůnek, Milan ; Brabec, Tomáš
There is no need to emphasize strongly the economical aspect of gas consumption forecasting in current conditions of price formation for distributive companies. One of the ways how to improve forecasting quality is the use of computer systems both for automatic time series forecasting, and also for decision support systems with an interactive feedback connection that can help experts (dispatchers, economists) in their decision, planning and control processes.
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Aplikace procedury Ac4ft-Miner na medicínská data
Nekvapil, Viktor ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
This bachelor thesis deals with the data mining procedure Ac4ft-Miner, implemented in the LISp-Miner system, which is developed at the Department of Information and Knowledge Engineering at the University of Economics, Prague. The aim of this thesis is firstly to describe the procedure in a simple, understandable way. Secondly, the aim is to apply this procedure on the medical data and present examples of use of this procedure. Further aim is to create methodology of use for doctors from the experience obtained. The aims are reached by using a lot of examples, which demonstrate theoretical concepts on concrete data and by the pursuit of the simple visualisation of tasks (analytical questions) solved by the procedure. The output of this thesis is a coherent text with lot of examples separated from the continuous text; so the reader familiar with a particular topic can skip the examples and proceed to the next issue. Further result of this thesis is an outline of the graphical presentation of analytical questions. Both the examples and the graphical presentation will be used further in the SEWEBAR project of which this thesis is one part. The methodology of use of the procedure for doctors is in the form of advices for use of the tool which should contribute to the further research which is needed. This is because of the high complexity of the procedure, which does not allow formulating general conclusions usable in the methodology. Chapter 1 characterizes the overall process of Knowledge Discovery in Databases represented by the CRISP-DM Methodology. Chapter 2 presents theoretical concepts related to Ac4ft-Miner. Chapter 3 deals with action rules. Chapter 4 addresses possibilities of defining the input and interpretation of the output of the Ac4ft-Miner. Chapter 5 describes the research conducted on the real medical data set ADAMEK, states methodology and examples of the output. Chapter 6 summarises the experience obtained and formulates the methodology of use of Ac4ft-Miner for doctors.
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Testing the procedure Ac4ft-Miner
Jedlička, Tomáš ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
Bachelor thesis focuses on testing the procedure Ac4ft-Miner. The aim of the thesis is to present this procedure, to suggest possibilities of its application and demonstrate them on apposite examples. Ac4ft-Miner is a new GUHA procedure that allows mining for G-action rules. It is an approach to action rules based on the GUHA method and its implementation in the LISp-Miner system. Basic types of G-action rules are defined in this work. Specific examples for each type and their interpretation and application are given, including possible problems and their solutions. Then results of this analysis are compared with a definition of the action rules. The input of the procedure Ac4ft-Miner is further described and in the end the procedure is applied for solving an analytical question.
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Knowledge base, analytical questions, LISp-Mner system and ADAMEK data
Kubín, Richard ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
The steps associated with the analytical question solving in terms of LISp-Miner system in ADAMEK medical data are the theme of this thesis. The operating sequence of using 4ft-Miner and SD4ft-Miner procedures in ADAMEK data together with the possibility of further use of formalized background knowledge and preparing routing for automatization of the downrighted steps are the objectiv of this thesis. The summary of the basic concepts and axioms of association rules and GUHA method is the content of the theoretical part of the thesis. Operativ part starts from CRISP-DM methodology. The operating sequence enabling searching for interesting association rules in different data, that is applied on STULONG medical data afterwards in order to get instigations for it's revision, is the produce of this thesis. Used data that come from EuroMISE are concern with cardiological patients.
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