This thesis surveys on problems preprocessing data. Forepart deal with view and description characteristic tests for description attributes, methods for work with data and attributes. Second part work describes work with program Rapidminer. It pays pay attention to single functions preprocessing in this programme describes their function. Third part equate to results with using methods preprocessing and without using data preprocessing.

This thesis is involved in image processing of medical data and its implementation using Java programming language. The main contribution of this thesis is creation of algorithms for feature extraction from 3D data and subsequent verification of the results for the issue of imagining 3D brain data, and creation of image filters and their implementation in the program RapidMiner. Consequently, the segmentation process is created at the 2D and 3D level, and output of 3D level segmentation are segmented brain structures. Furthermore, segmentation algorithms were compared on the basis of the final form of segmented structures and this approach was compared with other works.

The aim of the thesis was to study and describe data mining methodology CRISP-DM. From the collected database of calls to the call center a prediction was performed, based on CRISP-DM methodology. In phase of test situation modeling four different testing methods were used: the k-NN, neural network, linear regression and super vector machine. The input attributes importance for further prediction was evaluated based on different selections. The results and findings may provide data for further more accurate forecasts in the future; not only in number of calls but also other indicators relevant to the call center.

This thesis discusses the options households have when it comes to investing in capital markets in the Czech Republic. The issue of investing and capital market options is analyzed. Following this analysis comes the description of financial instruments, their characteristics, and the usability of these instruments by small investors. On the basis of the theory presented, a study was conducted to examine the usage of individual financial products. The collected data was processed using modern software tools, which helped in drawing several conclusions, results, and recommendations for investors and financial instrument providers alike.

This thesis focuses on creation and comparison of ice hockey matches prediction models with the view on ice hockey world championship matches. The first part is dedicated to collecting theoretical knowledge needed for solving this problem and the second to applying this set of knowledge. The model creation approach is intertwined with the CRISP-DM data mining methodology, which also defines several chapters of this work. As input data for the models I used performance statistics of individual ice hockey players -- this brought me to implementing a script capable of automatic downloading and aggregating of player data from the Internet. Downloaded data were arranged so as they would represent ice hockey matches that were played during the championships (team A consisting of players X against team B consisting of players Y) with result of the match added to the data row. Data were also analyzed to detect any quality issue prior to the model creation and transformed into an integrated view. Result assessment consists of two parts, in the first the technical evaluation of models using data from the testing data set takes place. The first part also points out practical usefulness of the models. The next part is about comparing result data with the betting odds -- the business relevance of the model. This part uses open source data about betting odds listed on the corresponding matches. Finally, the outcome model is used for predicting matches of the group phase of the world championship taking place in Prague, 2015.

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.

The main goal of this paper is the identification of comments on internet websites. The theoretical part is focused on artificial intelligence, mainly classifiers are described there. The practical part deals with creation of training database, which is formed by using generators of features. A generated feature might be for example a title of the HTML element where the comment is. The training database is created by input of classifiers. The result of this paper is testing classifiers in the RapidMiner program.

This diploma thesis presents description on several algorithms for decision trees induction and software RapidMiner. The first part of the thesis deals with partition and terminology of decision trees. There’re described all algorithms for decision tree construction in RapidMiner. The second part deals with implementation and comparison of chosen algorithms. The application was developed in C++. Based on the real datesets the comparisson of different algorithms was realized using Rapid Miner 4.0.

Made available in DSpace on 2016-08-03T12:30:10Z (GMT). No. of bitstreams: 1 Leandro Tavares2.pdf: 1287442 bytes, checksum: 7f5aa84748d1a824abe72b2b6940ffe2 (MD5) Previous issue date: 2014-09-09 / The work analyzes the media in the context of the Internet and outlines new methodologies for the study area in filtering meanings in the scientific realm of information flows from social networks, news media or any other device that allows storage and retrieval of structured information and unstructured. In an attempt to reflect on the ways that these information flows and develop mainly in the volume produced, the project scales the fields of meanings that this relationship appears in the theories and practices of research. The aim of this study is to contextualize the media area within a changing and dynamic reality that is the environment of the internet and make parallel before the applications already successful in other areas. With the method of case study three cases were analyzed under two conceptual keys to Web Sphere Analysis and the Web Science reflecting the opposing information systems in the discursive and structural aspect. This way observes what the Media has earned in order to view its objects of study in the environment of internet networks for these prospects. The research result shows that it is a challenge to the researcher Media seek new learning, but the feedback information in a collaborative environment that the Internet presents is fertile ground for research path, for data modeling wins analytical corpus when the set of tools promoted and driven by technology allows isolating contents and allows deepening the meanings and relationships. / O trabalho desenvolvido analisa a Comunicação Social no contexto da internet e delineia novas metodologias de estudo para a área na filtragem de significados no âmbito científico dos fluxos de informação das redes sociais, mídias de notícias ou qualquer outro dispositivo que permita armazenamento e acesso a informação estruturada e não estruturada. No intento de uma reflexão sobre os caminhos, que estes fluxos de informação se desenvolvem e principalmente no volume produzido, o projeto dimensiona os campos de significados que tal relação se configura nas teorias e práticas de pesquisa. O objetivo geral deste trabalho é contextualizar a área da Comunicação Social dentro de uma realidade mutável e dinâmica que é o ambiente da internet e fazer paralelos perante as aplicações já sucedidas por outras áreas. Com o método de estudo de caso foram analisados três casos sob duas chaves conceituais a Web Sphere Analysis e a Web Science refletindo os sistemas de informação contrapostos no quesito discursivo e estrutural. Assim se busca observar qual ganho a Comunicação Social tem no modo de visualizar seus objetos de estudo no ambiente das internet por essas perspectivas. O resultado da pesquisa mostra que é um desafio para o pesquisador da Comunicação Social buscar novas aprendizagens, mas a retroalimentação de informação no ambiente colaborativo que a internet apresenta é um caminho fértil para pesquisa, pois a modelagem de dados ganha corpus analítico quando o conjunto de ferramentas promovido e impulsionado pela tecnologia permite isolar conteúdos e possibilita aprofundamento dos significados e suas relações.

This work deals with the representation of segmented images using graphs. Different segmentation methods used in processing visual information are described here. Today is mathematics increasingly needed. This fact is not omitted, basic information of graph theory are described in this paper. The second part of this work is practical. It contains a survey of libraries processing graphs. Further the data structures for describing the segmented image are described. Last but not least, there is also described the formation and properties of the operators designed for environment RapidMiner that fill these structures.