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Statistical Classification Methods
Barvenčík, Oldřich ; Žák, Libor (referee) ; Michálek, Jaroslav (advisor)
The thesis deals with selected classification methods. The thesis describes the basis of cluster analysis, discriminant analysis and theory of classification trees. The usage is demonstrated by classification of simulated data, the calculation is made in the program STATISTICA. In practical part of the thesis there is the comparison of the methods for classification of real data files of various extent. Classification methods are used for solving of the real task – prediction of air pollution based of the weather forecast.
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Statistical image analysis in quality control
Legát, David
Title: Statistical image analysis in quality control Author: David Legát Department: Department of probability and mathematical statistics Supervisor: Prof. RNDr. Jaromír Antoch, CSc. Abstract: Currently, necessity to handle unstructured data rises significantly. One important area of unstructured data manipulation is signal processing such as audio and video, for which there exist many procedures. This work deals with the statistical approach to image processing, in which the image is interpreted as a representative of a random field. It describes two problems: removing noise from an image which facilitates better interpretation of the image, and image classification, in which we try to identify and recognize objects displayed. Part of the work aimed at eliminating of noise deals primarily with the use of MCMC simulation methods. These procedures can be tested in software that is included. Part of the work dealing with the classification of the image describes various modifications of classification trees methods. An example of image processing, which is the identification of defects in woven fabrics, is presented at the end. 1
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Predikcia bankrotu podnikov v sektore stavebníctva EÚ
Oberfrancová, Romana
This diploma thesis main goal is to predict primary bankruptcy indicators in construction sector based on model. This model is built by advanced classifier methods such as classification trees and logistic regression. Applicability of prediction depends on quality of built model and therefore verification of classification accuracy is essential for bankruptcy prediction. The theoretical part is focused on construction sector in the EU specializing on basic financial analysis including ratio indicators and frequently used models for predicting the bankruptcy of enterprises. The practical part consists of model creation and evaluation for each observed time period. The end of thesis is dealing with model evaluation based on given criteria.
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Telekomunikačný trh krajín V4
Hanková, Lucia
Hanková, L. Telecommunication sector in the Visegrad group countries. Diploma thesis. Brno: Mendel university, 2018. This diploma thesis analyses telecommunication sector of the Visegrad group countries. The aim of this thesis is to describe specifics and risks of this particular sector and uses classic and alternative financial ratios to compare performance and financial stability of the companies. In the theoretical part, each state´s tele-com sector is described as well as the methods and procedures used in this thesis. In the practical part, all of the financial ratios are calculated and classification trees for years 2012 - 2015 are built. Results are commented on statistical and economical level.
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Statistical image analysis in quality control
Legát, David
Title: Statistical image analysis in quality control Author: David Legát Department: Department of probability and mathematical statistics Supervisor: Prof. RNDr. Jaromír Antoch, CSc. Abstract: Currently, necessity to handle unstructured data rises significantly. One important area of unstructured data manipulation is signal processing such as audio and video, for which there exist many procedures. This work deals with the statistical approach to image processing, in which the image is interpreted as a representative of a random field. It describes two problems: removing noise from an image which facilitates better interpretation of the image, and image classification, in which we try to identify and recognize objects displayed. Part of the work aimed at eliminating of noise deals primarily with the use of MCMC simulation methods. These procedures can be tested in software that is included. Part of the work dealing with the classification of the image describes various modifications of classification trees methods. An example of image processing, which is the identification of defects in woven fabrics, is presented at the end. 1
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Statistical Classification Methods
Barvenčík, Oldřich ; Žák, Libor (referee) ; Michálek, Jaroslav (advisor)
The thesis deals with selected classification methods. The thesis describes the basis of cluster analysis, discriminant analysis and theory of classification trees. The usage is demonstrated by classification of simulated data, the calculation is made in the program STATISTICA. In practical part of the thesis there is the comparison of the methods for classification of real data files of various extent. Classification methods are used for solving of the real task – prediction of air pollution based of the weather forecast.
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Classification and Regression Trees in R
Nemčíková, Lucia ; Bašta, Milan (advisor) ; Vilikus, Ondřej (referee)
Tree-based methods are a nice add-on to traditional statistical methods when solving classification and regression problems. The aim of this master thesis is not to judge which approach is better but rather bring the overview of these methods and apply them on the real data using R. Focus is made especially on the basic methodology of tree-based models and the application in specific software in order to provide wide range of tool for reader to be able to use these methods. One part of the thesis touches the advanced tree-based methods to provide full picture of possibilities.
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Usage classification trees in market analysis
PROKOPOVÁ, Kateřina
In my thesis I dealt with usage classification trees in market analysis, whereas I focused on area providing mobile services. The aim of my work was, by use of progressive methodology CART (classification and regression trees), to identify important factors biasing consumer behavior. On the basis of this questionnaire inquiry I have came the opinion, that consumers purchase mobile phone services base on their net monthly income, age, occupation, services required and whether they use the mobile service for personal or business purposes.
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