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Data Mining on Oracle Database Server and MS SQL Server
Opršal, Martin ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This bachelor's thesis deals with issue of knowledge discovery in databases. This document is focused in getting rules from relation databases based on Microsoft SQL server or Oracle Data mining server. The practical part of this document is about design applications that run on both servers. These applications are programmed in asp.NET, C# for Microsoft SQL server and Java for Oracle server.
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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 Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
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Integration, Visualization, and Mining from Data of World Countries
Dušek, Vladimír ; Rychlý, Marek (referee) ; Bartík, Vladimír (advisor)
This thesis explores the utilization of open data about countries around the world, particularly data in the areas of progress and quality of life. The goal was to design and implement a web application to present this data and further use the data for data mining. The integration and processing of data from open data sources were accomplished using the Apache Airflow platform. The Python framework FastAPI was used to create the API and the JavaScript library ReactJS was used to implement the web application. In the application, the indicators are categorized. Each of them can be displayed for different groups of countries, for different time periods, and in several visualizations. From the domain of data mining, clustering of countries based on a group of indicators and prediction of future development of selected indicators using regression analysis was performed. The final application is available at jakjsmenatom.cz.
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Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
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Comparation of Models for Datamining
Pospíšil, Jan ; Bartík, Vladimír (referee) ; Lukáš, Roman (advisor)
This thesis focuses on comparing of the datamining models features depending on the different databazis topology. The objekt was to find key features that at most involve the accuracy of classification. Thesis is composed from chapters in a way that even a non-professional or even a complete laik could understand the object and could find theese thesis results useful. In the beginning the reader is beeing made familiar with all the background information about datamining and its models and algorithms, the second part denotes about the model comparison and discusses its results.
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Integration, Visualization, and Mining from Data of World Countries
Dušek, Vladimír ; Rychlý, Marek (referee) ; Bartík, Vladimír (advisor)
This thesis explores the utilization of open data about countries around the world, particularly data in the areas of progress and quality of life. The goal was to design and implement a web application to present this data and further use the data for data mining. The integration and processing of data from open data sources were accomplished using the Apache Airflow platform. The Python framework FastAPI was used to create the API and the JavaScript library ReactJS was used to implement the web application. In the application, the indicators are categorized. Each of them can be displayed for different groups of countries, for different time periods, and in several visualizations. From the domain of data mining, clustering of countries based on a group of indicators and prediction of future development of selected indicators using regression analysis was performed. The final application is available at jakjsmenatom.cz.
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Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
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Data Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
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|
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Data Mining on Oracle Database Server and MS SQL Server
Opršal, Martin ; Chmelař, Petr (referee) ; Stryka, Lukáš (advisor)
This bachelor's thesis deals with issue of knowledge discovery in databases. This document is focused in getting rules from relation databases based on Microsoft SQL server or Oracle Data mining server. The practical part of this document is about design applications that run on both servers. These applications are programmed in asp.NET, C# for Microsoft SQL server and Java for Oracle server.
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