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Creation of New Prediction Units in Data Mining System on NetBeans Platform
Havlíček, David ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
The issue of this master's thesis is a creation of new prediction unit for existing system of knowledge discovery in database. The first part of project deal with general problems of knowledge discovery in database and predictive analysis. The second part of the project deal with system developed on FIT, for which is module implemented, used technologies, concept and implementation of mining module for this system. The solution is implemented in Java language and is a built on the NetBeans platform.
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Data Mining System in Oracle
Krásný, Michal ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This MSc Project deals with the system of Knowledge Discovery in Databases. It is a client application which uses the Oracle Data Mining Server's 10.g Release 2 (10.2) services. The application is implemented in Java, the graphical user interface is built on the NetBeans Rich Client Platform. The theoretical part introduces the Knowledge Discovery in Databases, while the practical part describes functionality of the original system, it's deficiencies, documents sollutions of theese deficiencies and there are proposed improvements for further development. The goal of this project is to modify the system to increase the application usability.
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Data Independency of the FIT-Miner Data Mining System
Novák, Ondřej ; Šebek, Michal (referee) ; Zendulka, Jaroslav (advisor)
System for data mining Fit-Miner is now dependant on only one specific DBMS. This master’s thesis deals with analysis of implementation that works with database, modules and functions for data mining. Next it shows the set of changes which will allow FIT-Miner to work with another DBMS. And finally, a description of the implementation of these changes.
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Mining Modules of the Data Mining System in Oracle
Mader, Pavel ; Křivka, Zbyněk (referee) ; Zendulka, Jaroslav (advisor)
This master's thesis deals with questions of the data mining and an extension of a data mining system in the Oracle environment developed at FIT. So far, this system cannot apply to real-life conditions as there are no data mining modules available. This system's core application design includes an interface allowing the addition of mining modules. Until now, this interface has been tested on a sample mining module only; this module has not been executing any activity just demonstrating the use of this interface. The main focus of this thesis is the study of this interface and the implementation of a functional mining module testing the applicability of the implemented interface. Association rule mining module was selected for implementation.
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Mining Modules of Data Mining System on NetBeans Platform
Henkl, Tomáš ; Lukáš, Roman (referee) ; Zendulka, Jaroslav (advisor)
The master's thesis deals with the knowledge discover in databases and with the extending of the data mining systems in the Oracle environment developed at the VUT FIT. The system kernel conception incorporates an interface that enables the adding of data mining modules. The objective of the thesis is to learn this interface and implement and embed the data mining module for decision-tree classification into the application. In addition, the thesis compares the application with similar commercial product SAS Enterprise Miner
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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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Data Mining Module
Petrlík, Jiří ; Fiala, Jiří (referee) ; Zendulka, Jaroslav (advisor)
The aim of the bachelor's theses is to introduce the problematic of data mining. I have especially focused on the problematic of the classification with the help of neural networks. This is why I describe some basic algorithms for neural network teaching as well. The main goal of this work is to create a new module for the system of data mining. This system has been developed in the cooperation with other people from FIT VUT in Brno. I introduce this system here as well and I also describe the proposal for it' s new module. I have already tested some training data with the final module.
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Data Mining Module
Hlosta, Martin ; Stryka, Lukáš (referee) ; Zendulka, Jaroslav (advisor)
This thesis concerns knowledge discovery in databases (KDD), especially classification by Support Vector Machines (SVM). System for KDD has been developed at FIT BUT. For KDD process description is used language DMSL. The goal of the thesis was to extend DMSL with respect to SVM classifier, propose, implement and test a module for this system.
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Functionality Extension of Data Mining System on NetBeans Platform
Šebek, Michal ; Zendulka, Jaroslav (referee) ; Lukáš, Roman (advisor)
Databases increase by new data continually. A process called Knowledge Discovery in Databases has been defined for analyzing these data and new complex systems has been developed for its support. Developing of one of this systems is described in this thesis. Main goal is to analyse the actual state of implementation of this system which is based on the Java NetBeans Platform and the Oracle database system and to extend it by data preprocessing algorithms and the source data analysis. Implementation of data preprocessing components and changes in kernel of this system are described in detail in this thesis.
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Cluster Analysis Module of a Data Mining System
Hlosta, Martin ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with the design and implementation of a cluster analysis module for currently developing datamining system DataMiner on FIT BUT. So far, the system lacked cluster analysis module. The main objective of the thesis was therefore to extend the system of such a module. Together with me, Pavel Riedl worked on the module. We have created a common part for all the algorithms so that the system can be easily extended to other clustering algorithms. In the second part, I extended the clustering module by adding three density based clustering aglorithms - DBSCAN, OPTICS and DENCLUE. Algorithms have been implemented and appropriate sample data was chosen to verify theirs functionality.
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