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Coupling of images
Gorgol, Martin ; Petyovský, Petr (referee) ; Richter, Miloslav (advisor)
This master’s thesis describes the design and implementation of the application that created the basis set pieces "puzzle" according to the shape of the folded edges of the original image. This application is developed using Matlab. The work also describes how to create a database of actual pieces of the puzzle composite photo image. Closer was also focused on finding the characteristic section points, their segmentation and appropriate description. There is dismantled procedure for selecting the types of symptoms and their extraction. On the basis of suitably described pieces of segmented parts is designed and implemented the algorithm of comparing and grouping into clusters. Using the proposed method of visualization is then displayed in the resulting composite picture puzzle.
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Difficulty of Preparing Self-Service BI Environment
Píhrt, Tomáš ; Gála, Libor (advisor) ; Pour, Jan (referee)
The aim of this thesis was to evaluate the difficulty of preparing the environment for business intelligence tools, namely self-service which shows a growing potential in this field. Starting point was the analysis of existing methodologies, procedures and recommendations for preparing BI environment, furthermore the analysis of factors that affect the process of preparation. In order to verify the differences between self-service BI products were defined a methodology and criteria which were relevant for evaluation. The evaluation of Top 5 BI products was examined based on the evaluation model and using specific data set from a small business company environment.
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Automation of data preprocessing using domain knowledge
Beskyba, Jan ; Šimůnek, Milan (advisor) ; Pejčoch, David (referee)
In this work we propose a solution that would help automate the part of knowledge discovery in databases. Domain knowledge has an important role in the automation process which is necessary to include into the proposed program for data preparation. In the introduction to this work, we focus on the theoretical basis of knowledge discovery of databases with an emphasis on domain knowledge. Next, we focus on the basic principles of data pre-processing and scripting language LMCL that could be part of the design of the newly established applications for automated data preparation. Subsequently, we will deal with application design for data pre-processing, which will be verified on the data the House of Commons.
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Implementation of data preparation procedures for RapidMiner
Černý, Ján ; Berka, Petr (advisor) ; Kliegr, Tomáš (referee)
Knowledge Discovery in Databases (KDD) is gaining importance with the rising amount of data being collected lately, despite this analytic software systems often provide only the basic and most used procedures and algorithms. The aim of this thesis is to extend RapidMiner, one of the most frequently used systems, with some new procedures for data preprocessing. To understand and develop the procedures, it is important to be acquainted with the KDD, with emphasis on the data preparation phase. It's also important to describe the analytical procedures themselves. To be able to develop an extention for Rapidminer, its needed to get acquainted with the process of creating the extention and the tools that are used. Finally, the resulting extension is introduced and tested.
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