| |
|
Estimation and goodness-of-fit criteria in logistic regression model
Ondrušková, Markéta ; Hanzák, Tomáš (advisor) ; Zvára, Karel (referee)
In this bachelor thesis we describe binary logistic regression model and estimation of model's parameters by maximum likelihood method. Then we propose algorithm for the least squares method. In the goodness-of-fit criteria part we define Lorenz curve, Gini coefficient, C-statistics, Kolmogorov-Smirnov statistics and coefficient of determination R2 . We derive their relation to different sample coefficients of correlation. We derive typical relation between Gini coeffi- cient, Kolmogorov-Smirnov statistics and newly also coefficient of determination R2 via model of normally distributed score of bad and good clients. These derived teoretical results are verified on three real data sets. Keywords: Binary logistic regression, maximum likelihood, ordinary least squa- res, Gini coefficient, coefficient of determination. 1
|
|
Výpočet radiace v lesních porostech na základě dat leteckého laserového skenování
Patočka, Zdeněk
Leaf area index (LAI) is the most important variable influencing the penetration of solar radiation beams through the forest stand. Currently, the airborne laser scanning, as new indirect method, suggests itself for estimation of LAI. LAI was measured terrestrially using the hemispherical photographies analysis and compared with LiDAR Penetration Index - LPI. There were created several regression models describing the dependence of LAI and LPI with coefficients of determination from 0.71 up to 0.81. Leaf area index was also applied to the Beer-Lambert law for calculation of the solar radiation in forest stands. Practical application possibilities of LPI in forestry (estimation of stocking, optimization of shelterwood cuttings etc.) have been described in conclusion of this diploma thesis.
|
|
Symbolic Regression and Coevolution
Drahošová, Michaela ; Žaloudek, Luděk (referee) ; Sekanina, Lukáš (advisor)
Symbolic regression is the problem of identifying the mathematic description of a hidden system from experimental data. Symbolic regression is closely related to general machine learning. This work deals with symbolic regression and its solution based on the principle of genetic programming and coevolution. Genetic programming is the evolution based machine learning method, which automaticaly generates whole programs in the given programming language. Coevolution of fitness predictors is the optimalization method of the fitness modelling that reduces the fitness evaluation cost and frequency, while maintainig evolutionary progress. This work deals with concept and implementation of the solution of symbolic regression using coevolution of fitness predictors, and its comparison to a solution without coevolution. Experiments were performed using cartesian genetic programming.
|
|
The labour market in České Budějovice district in relation with education
SEDLÁK, Jiří
This thesis deals with the labour market in České Budějovice district in relation with education. The first section provides basic theoretical background of the labour market followed by the issue of human capital, where education plays an important role. At the end of the first part, the current situation and possible developments of the labour market in the Czech Republic with relation to education are described. In the practical part, the introduced region is analyzed with respect to the labour market. Using a questionnaire survey distributed among companies of the region were obtained relevant data, which reflect the current situation of graduates at the local labour market. Finally, there is a multiple regression model, which is created based on testing a limited group of employees to determine, whether the investment in education is really profitable. At the end of this work, problem areas are defined and evaluated.
|
|
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.
|
| |
| |
|
Monitoring and comparison of the main operational and economic parameters of a selected group of tractors
VOJTA, Luboš
In my thesis, I paid attention to one of the operational and economic aspects concerning the operation of tractors or their cost of repairs and maintenance. For this work was selected group of brands of tractors and McCormick MTX and XTX series. Because the work was to compare growth in the cost of repairs and maintenance, depending on years of operation, it was first necessary to determine the two variables and the cost of repairs and maintenance and years of operation. Then were analyzed by statistical methods of correlation, regression, variance and standard deviation.
|
| |
guest ::
