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Datamining on publicly accessible data
Pangrác, Jiří ; Rauch, Jan (advisor) ; Chudán, David (referee)
This bachelor thesis deals with the datamining methods on publicly accessible data. Data mining is a technique of mining potentially interesting relations from data. Analysis is carried out on data provided by Česká obchodní inspekce, the czech office for trade inspection, which are accessible to public. I am trying to find possible answers for some analytical questions asked. For the analysis itself, LISp-Miner system was used focusing on 4ft-Miner and CF-Miner procedures. Besides the actual analysis, this thesis includes a brief description of LISp-Miner system and datamining generally. The main goal of this work is presentation of the results for their possible practical use.
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Vytvoření predikčního modelu předpovědi počasí pomocí neuronové sítě a asociačních pravidel
Kadlec, Jakub ; Rauch, Jan (advisor) ; Berka, Petr (referee)
This diploma thesis introduces three different methods of creating a neural network binary classifier for the purpose of automated weather prediction with attribute pre-selection using association rules and correlation patters mining by the LISp-Miner system. First part of the thesis consists of collection of theoretical knowledge enabling the creation of such predictive model, whereas the second part describes the creation of the model itself using the CRISP-DM methodology. Final part of the thesis analyses the performance of created classifiers and concludes the proposed methods and their possible benefits over training the network without attribute pre-selection.
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Options of presentation of KDD results on Web
Koválik, Tomáš ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
This diploma thesis covers KDD analysis of data and options of presentation of KDD results on Web. The paper is divided into three main sections, which follow the whole process of this thesis. In the first section are mentioned theoretical basics needed for understanding of discussed problem. In this section are described notions data matrix and domain knowledge, concept of CRISP-DM methodology, GUHA method, system LISp-Miner and implementation of GUHA method in LISp-Miner including description of core procedures 4ft-Miner and CF-Miner. The second section is dedicated to the first goal of this paper. It briefly summarizes analysis made during pre-analysis phase. Then is described process of analysis of domain knowledge in a given data set. The third part focuses on the second goal of this thesis, which is problem of presentation of KDD results on Web. This section covers brief theoretical basis for used technologies. Then is described development of export script for automatic generation of website from results found using LISp-Miner system including description of structure of the output and recommendations for work in LISp-Miner system.
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Use of data mining techniques for open data
Prokůpek, Miroslav ; Rauch, Jan (advisor) ; Chudán, David (referee)
This diploma thesis examines applications of datamining methods to open data. It is realized by solving analytical questions using the LISp-Miner system. Analytical questions are examined in data from The Czech Trade Inspection Authority from the perspective of the data owner. Procedure used to solve analytical questions is 4ft-Miner. There are presented and resolved four analytical questions, which are the results of the work. Work includes a detailed description of the transformation of the relational database into a format suitable for data mining. A detailed description of the data is also included. The theoretical part deals with the GUHA method and CRISP-DM methodology.
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Analysis of the real data from the restaurant sector
Šimeček, Petr ; Rauch, Jan (advisor) ; Šimůnek, Milan (referee)
The aim of this thesis is to analyze the real data from the restaurant sector in the center of Prague, prove assumptions based on existing knowledge and explore hidden relations. The database management system MySQL was used for the initial transformation of the original data structure. The data after the transformation were converted into a form that it was possible to manipulate with it using the procedure LMDataSource of the system LISp-Miner. The analysis of association of relations were used for the procedure 4ft-Miner of the system LISp-Miner. The MySQL database system was used for the frequency analysis to obtain results, and Microsoft Word and Excel were used to interpret the results. Some of the assumptions in the research were found proven. Furthermore, an interesting combination of relations was discovered. The output of this work allows the owner of the data to use some of the data analysis results for the optimization of internal processes. In addition, this study points out other possible ways to analyze these data.
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Application of KDD on the data of plastic surgery clients
Šotlík, Jakub ; Rauch, Jan (advisor) ; Tomášek, David (referee)
The main objective of my thesis is to analyze data about clients of plastic and aesthetic surgery with methods and tools of the Knowledge Discovery in Databases and to find as many useful knowledge as possible from the data's owner view (the knowledge consists of verbal rules expressing relationships between two entities). Found knowledge will be presented in SEWEBAR system. Elaboration of my work is in accordance with CRISP-DM methodology that is used for the Knowledge Discovery in Databases. Analytical questions will be solved by LISp-Miner software that uses analytical procedure 4ft-Miner of the GUHA method. Found relationships will be presented in SEWEBAR system and some interesting relationships will be presented in this work. The main purpose of the thesis is to find useful knowledge of plastic and aesthetic surgery branch from both business and medical view. From medical point of view the work finds knowledge about medical and psychological status of clients. From business point of view the work finds knowledge for management. The thesis is structured to correspond with CRISP-DM methodology where every phase of methodology has one chapter. There is result of every phase described in every chapter together with the description of my work on phase.
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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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