|
|
Factors influencing the satisfaction with facilities for PhD studies
Paul, Miroslav ; Vltavská, Kristýna (advisor) ; Milatová, Pavla (referee)
This diploma thesis deals with the satisfaction of PhD students with facilities for the study by means of data gained from DOKTORANDI 2014 survey. The aim of the thesis is to identify factors that influence the satisfaction with facilities for PhD studies and finding similarities among different fields of studies according to satisfaction with facilities. The first part of this thesis contains a description of higher education with a focus on PhD programs and a description of statistical methods that are subsequently used in analytical part and a description of DOKTORANDI 2014 survey. The analytical part aims to answer the questions which factors affect the PhD students´ satisfaction with facilities for study using logistic regression and decision trees. Further it tries to determine the satisfaction similarities of PhD study fields with facilities for studying using cluster analysis.
|
|
|
Employability of graduates of the University of Economics, Prague and their quality assessment of acquired higher education
Dejl, Lukáš ; Vltavská, Kristýna (advisor) ; Hulík, Vladimír (referee)
This diploma thesis deals with the employability of graduates of the University of Economics, Prague (UE) and their quality assessment of acquired higher education based on REFLEX 2013 survey. The first part of this thesis is focused on theoretical concepts and statistical methods that are subsequently used in analytical part. The analytical part contains analysis of UE graduates employability and the quality assessment of acquired higher education. The aim of this diploma thesis is to provide answers on whether there is a relationship between studied faculty and job classification or which factors affect the monthly wage level using the multidimensional statistical methods. The thesis also deals with the graduates evaluation of acquired knowledge applicability and practical usability in future career.
|
|
|
Building credit scoring models using selected statistical methods in R
Jánoš, Andrej ; Bašta, Milan (advisor) ; Pecáková, Iva (referee)
Credit scoring is important and rapidly developing discipline. The aim of this thesis is to describe basic methods used for building and interpretation of the credit scoring models with an example of application of these methods for designing such models using statistical software R. This thesis is organized into five chapters. In chapter one, the term of credit scoring is explained with main examples of its application and motivation for studying this topic. In the next chapters, three in financial practice most often used methods for building credit scoring models are introduced. In chapter two, the most developed one, logistic regression is discussed. The main emphasis is put on the logistic regression model, which is characterized from a mathematical point of view and also various ways to assess the quality of the model are presented. The other two methods presented in this thesis are decision trees and Random forests, these methods are covered by chapters three and four. An important part of this thesis is a detailed application of the described models to a specific data set Default using the R program. The final fifth chapter is a practical demonstration of building credit scoring models, their diagnostics and subsequent evaluation of their applicability in practice using R. The appendices include used R code and also functions developed for testing of the final model and code used through the thesis. The key aspect of the work is to provide enough theoretical knowledge and practical skills for a reader to fully understand the mentioned models and to be able to apply them in practice.
|
|
|
Methods for class prediction with high-dimensional gene expression data
Šilhavá, Jana ; Matula, Petr (referee) ; Železný, Filip (referee) ; Smrž, Pavel (advisor)
Dizertační práce se zabývá predikcí vysokodimenzionálních dat genových expresí. Množství dostupných genomických dat významně vzrostlo v průběhu posledního desetiletí. Kombinování dat genových expresí s dalšími daty nachází uplatnění v mnoha oblastech. Například v klinickém řízení rakoviny (clinical cancer management) může přispět k přesnějšímu určení prognózy nemocí. Hlavní část této dizertační práce je zaměřena na kombinování dat genových expresí a klinických dat. Používáme logistické regresní modely vytvořené prostřednictvím různých regularizačních technik. Generalizované lineární modely umožňují kombinování modelů s různou strukturou dat. V dizertační práci je ukázáno, že kombinování modelu dat genových expresí a klinických dat může vést ke zpřesnění výsledku predikce oproti vytvoření modelu pouze z dat genových expresí nebo klinických dat. Navrhované postupy přitom nejsou výpočetně náročné. Testování je provedeno nejprve se simulovanými datovými sadami v různých nastaveních a následně s~reálnými srovnávacími daty. Také se zde zabýváme určením přídavné hodnoty microarray dat. Dizertační práce obsahuje porovnání příznaků vybraných pomocí klasifikátoru genových expresí na pěti různých sadách dat týkajících se rakoviny prsu. Navrhujeme také postup výběru příznaků, který kombinuje data genových expresí a znalosti z genových ontologií.
|
|
|
Building predictive models
ZABLOUDIL, Jakub
This mater thesis is focused on building predictive models. Their fundamental task is to provide an early-warning system, giving information about potential enterprise bankruptcy. The main essence and aim of the thesis is to create multivariate classification models by using discriminant analysis and logistic regression. Emphasis is put on their predictive accuracy, which is assessed for period of three years before bankruptcy declaration. Attempts to optimize classification thresholds in order to increase the initial accuracy are also made. Evaluating classification reliability of several existing models and performing profile analysis assessing predictive ability of univariate ratios were accomplished as well.
|
|
|
Evolutionary Design of Simulator Based on Cellular Automata
Brigant, Vladimír ; Šperka, Svatopluk (referee) ; Mrnuštík, Michal (advisor)
This work describes concept of a cellular automata (CA) simulator, which is able to predict behaviour of a complex spatial system. This prediction is based on available training data and transition rule acquired from regression analysis powered by evolutionary algorithms. Two regression analysis methods (linear and logistic regression) are suggested, implemented and compared on urban growth prediction of Brno city.
|
|
|
Deep Learning for Image Recognition
Munzar, Milan ; Kolář, Martin (referee) ; Hradiš, Michal (advisor)
Neural networks are one of the state-of-the-art models for machine learning today. One may found them in autonomous robot systems, object and speech recognition, prediction and many others AI tasks. The thesis describes this model and its extension which is used in an object recognition. Then explains an application of a convolutional neural networks(CNNs) in an image recognition on Caltech101 and Cifar10 datasets. Using this exemplar application, the thesis discusses and measures efficiency of techniques used in CNNs. Results show that the convolutional networks without advanced extensions are able to reach a 80\% recognition accuracy on Cifar-10 and a 37\% accuracy on Caltech101.
|
|
|
Statistical Classification by means of generalized linear models
Sladká, Vladimíra ; Mrázková, Eva (referee) ; Michálek, Jaroslav (advisor)
The goal of this thesis is introduce the theory of generalized linear models, namely probit and logit model. This models are especially used for medical data processing. In our concrete case these mentioned models are applied to data file obtained in teaching hospital Brno. The aim is statically analyzed immune response of child patients in dependence of twelve selected types of genes and find out which combinations of these genes influence septic state of patients.
|
|
|
Statistical Models of Success of Various Techniques of Rugby Kicking
Vrbacká, Kateřina ; Votavová, Helena (referee) ; Bednář, Josef (advisor)
This bachelor thesis is dealing with the testing of statistical hypothesis and their practical use. We model the success of rugby kicking and analyze the dominant factors (ball position, kicking technique, player) and their interactions. We will use some mathematical terms such as chi-square test of independence and logistic regression. The final model will be processed by software MINITAB. The outcome from this thesis will be the exact description of this situation.
|
|
|
The Estimation of Probability of Default Using Logistic Regression
Chalupa, Tomáš ; Dlouhá, Zuzana (advisor) ; Formánek, Tomáš (referee)
The aim of this work is to develop a suitable model that estimates a probability of default of client's loan. As estimation method was used a logistic regression and a probit regression and two definitions of default, 60 and 90 days overdue. The work describes the method of construction, estimation and testing of scoring models and a structure of dataset, which was used in the practical part. Firstly, it was created a theoretical model that was later confronted with estimates. Estimated models were compared by described statistics as McFadden R^2, the ability to diversify was investigated by the Lorenz curve and by the Gini coefficient. It was found that the logistic and the probit regressions have almost the same results, and that 90 days is preferable definition of default than 60 days.
|
guest ::
