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Knowledge Discovery in Object Relational Databases
Chytka, Karel ; Vrážel, Dušan (referee) ; Chmelař, Petr (advisor)
The goal of this master's thesis is to acquaint with a problem of a knowledge discovery and objectrelational data classification. It summarizes problems which are connected with mining spatiotemporal data. There is described data mining kernel algorithm SVM. The second part solves classification method implementation. This method solves data mining in a Caretaker trajectory database. This thesis contains application's implementation for spatio-temporal data preprocessing, their organization in database and presentation too.
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Graphical Layer for a Data Mining System
Gálet, Michal ; Burget, Radek (referee) ; Zendulka, Jaroslav (advisor)
The issue of this MSc. project is a design and implementation of a graphical user interface for a data mining system. The application is a front-end for an existing data mining library and allows the user to visually define the data mining process using a graphical editor and a component palette. The solution is built on a NetBeans Rich Client Platform and takes many benefits from using rich components available in this platform. The user may define his work in the projects, edit and persist DMSL documents, run the mining tasks and view the mining results. The system is designed to emphasize the modularity and extensibility of the solution.
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Use of Data Mining for Payment Identification
Bartoš, Stanislav ; Burget, Radek (referee) ; Bartík, Vladimír (advisor)
This master thesis concentrates on design and implementation of a system for payment identification, even if the reliable identifier (e.g. variable symbol) is missing. Data mining techniques, such as classification and prediction, were used as a solution to this problem. This master thesis is company assignment for company "Platební instituce Roger a.s.".
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Use of Knowledge Discovery for Data from PDF Files
Dvořáček, Libor ; Burgetová, Ivana (referee) ; Bartík, Vladimír (advisor)
This bachelor thesis deals with the extraction of tables from digitally created pdfs and the subsequent use of the obtained data for data analysis. Methods of dimension reduction and cluster analysis are used. The main content is an analysis of available tools for data extraction in the python language, a description and comparison of the used machine learning methods and implementation of an application that combines all these topics into one functional unit at: http://extraktor.herokuapp.com
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Data Mining with Python
Šenovský, Jakub ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this thesis was to get acquainted with the phases of data mining, with the support of the programming languages Python and R in the field of data mining and demonstration of their use in two case studies. The comparison of these languages in the field of data mining is also included. The data preprocessing phase and the mining algorithms for classification, prediction and clustering are described here. There are illustrated the most significant libraries for Python and R. In the first case study, work with time series was demonstrated using the ARIMA model and Neural Networks with precision verification using a Mean Square Error. In the second case study, the results of football matches are classificated using the K - Nearest Neighbors, Bayes Classifier, Random Forest and Logical Regression. The precision of the classification is displayed using Accuracy Score and Confusion Matrix. The work is concluded with the evaluation of the achived results and suggestions for the future improvement of the individual models.
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Expert systems in military
Stahl, Ladislav ; Ivánek, Jiří (advisor) ; Papík, Richard (referee)
This master thesis deals with the topic of expert systems in the military. In the first part, expert systems are described in general focusing on the theoretical aspects. The creation, types, structure, architecture, advantages, disadvantages and history of expert systems and knowledge acquisition are described. The next part of the thesis deals with the specific military and security (defence) applications of expert systems. There are descriptions of applications from Ground forces (ADRIES, ESROC, KBGIS, PRIDE, TED systems), Air forces (AIRID, LES, TATR), NAVY (systems BATTLE, SIAMES systems), Joint forces (AI-EOD, CMES, GTEX, MBEES, MCTA, SEAT SEC systems) and security areas (EPS-APES, DOC - EXPLOIT, FRIEND - FOE / FIRE DECISION systems). A more detailed description of ADRIES, BATTLE, KBGIS a FRIEND - FOE DETECTION / FIRE DECISION expert systems is included in the final part of the thesis.
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Prediction of Values on a Time Line
Maršová, Eliška ; Bařina, David (referee) ; Zemčík, Pavel (advisor)
This work deals with the prediction of numerical series whose application is suitable for prediction of stock prices. They explain the procedures for analysis and works with price charts. Also explains the methods of machine learning. Knowledge is used to build a program that finds patterns in numerical series for estimation.
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Time-Serie Mining Module of a Data Mining System
Klement, Ondřej ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The subject of this master's thesis is extension of existing data mining system. System will be extended by the module for the time series data mining. This thesis consists of common introduction to data mining issues and continues with time series analysis. Thesis then also contains some of the current tasks and algorithms used in time series data mining, follows by the concept of the implementation and description of the choosen mining method. Possible future system's improvments are disscused at the end of the paper.
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Knowledge Discovery in Databases of Moving Objects
Chovanec, Vladimír ; Mlích, Jozef (referee) ; Chmelař, Petr (advisor)
The aim of this master's thesis is to get familiar with problems of data mining and classification. This thesis also continues with application SUNAR, which is upgraded in practical part with SVM classification of persons passing between cameras. In the conclusion, we discuss ways to improve classification and person recognition in application SUNAR.
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Graphical Layer for a Data Mining System
Gálet, Michal ; Burget, Radek (referee) ; Zendulka, Jaroslav (advisor)
The issue of this MSc. project is a design and implementation of a graphical user interface for a data mining system. The application is a front-end for an existing data mining library and allows the user to visually define the data mining process using a graphical editor and a component palette. The solution is built on a NetBeans Rich Client Platform and takes many benefits from using rich components available in this platform. The user may define his work in the projects, edit and persist DMSL documents, run the mining tasks and view the mining results. The system is designed to emphasize the modularity and extensibility of the solution.
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