Use of cross-validation in selected classification methods

One of the aims of this thesis is to compare the methods of cross-validation, selected methods of classification and their mutual combinations on eight real datasets. Methods are compared by average rankings according to accuracy and area under the ROC curve, the duration of the whole process is compared as well. On average, logistic regression combined with ten times repeated ten-fold cross-validation proved to be the best classification method. The second aim of the thesis is to investigate the behaviour of cross-validation methods at different settings, specifically selection of the k parameter for k-fold cross validation and to split the dataset into the part for training and testing. Last but not least, the optimization of classification methods is investigated, specifically, an optimal boundary for the classification by logistic regression and avoidance overfitting in decision trees.Jedním z cílů této diplomové práce je porovnání metod krosvalidace, vybraných metod klasifikace a jejich vzájemných kombinací na osmi reálných datových souborech. Jednotlivé metody jsou porovnávány prostřednictvím průměrných pořadí podle celkové správnosti klasifikace a plochy pod ROC křivkou, porovnávána je i doba trvání. V průměru se jako nejlepší klasifikační metoda osvědčila logistická regrese v kombinaci s desetkrát opakovanou desetinásobnou krosvalidací. Druhým cílem práce je zkoumání chování metod krosvalidace při různém nastavení, konkrétně volba parametru k u k-násobné krosvalidace a rozdělení datového souboru na trénovací a testovací část. V neposlední řadě je v této práci zkoumána optimalizace klasifikačních metod, konkrétně optimální hranice pravděpodobnosti při klasifikaci pomocí logistické regrese a vyvarování tzv. přeučení rozhodovacích stromů

Contingency table analysis from questionnaire survey data of drivers

The bachelor thesis deals with the contingency table analysis from questionnaire survey data of drivers. The data were obtained from the agency Data Collect s.r.o., which conducted the survey in 2014. The aim of the thesis is to analyse the behaviour of drivers and their habits, which could increase the risk of accidents. The thesis is divided into two main parts; in the first one, methods of contingency table analysis are described; in the second one, the presented analyses are applied to the survey data. Firstly, the behaviour of single and young drivers is analysed, then the differences between men and women drivers. Calculations were made using the software SPSS and MS Excel, in which all the graphs and tables were made

Relationship between Patient Preferences, Attitudes to Treatment, Adherence, and Quality of Life in New Users of Teriflunomide

Background: A poor patient adherence often limits the real-world effectiveness of an oral disease-modifying therapy (DMT) for multiple sclerosis (MS). In the present study, we aimed to map patient preferences, attitudes toward treatment, and quality of life to identify the predictors of non-adherence to teriflunomide. Methods: This was a single-arm, non-interventional, multicenter study (Czech Act 378/2007 Coll.) consisting of three visits: the first at treatment initiation (teriflunomide 14 mg), and then after 3 and 9 months of therapy. We enrolled both DMT-naïve and patients who had undergone a DMT diagnosed with a clinically isolated syndrome (CIS) or relapsing-remitting multiple sclerosis (RRMS). The functional status and MS activity were estimated using the Expanded Disability Status Scale (EDSS) and annualized relapse rate (ARR); the quality of life via the Multiple Sclerosis Impact Scale (MSIS-29); the medication adherence with the Morisky Medication Adherence Scale (MMAS-8); the confidence in the ability to take medications by the Self-Efficacy for Appropriate Medication Score (SEAMS); and the attitude to the therapy via the Beliefs about Medicines Questionnaire (BMQ). After nine months of therapy, we predicted the adherence to teriflunomide (MMAS-8) by fitting a multivariate ordinal logistic model with EDSS changes, gender, previous DMT, MSIS-29, BMQ, and SEAMS as the explanatory variables. Results: Between 2018 and 2019, 114 patients were enrolled at 10 sites in the Czech Republic. The mean age was 41.2 years, 64.8% were diagnosed with a CIS, 52.4% were DMT-naïve, and 98.1% of patients preferred an oral administration at the baseline. The mean EDSS baseline was 1.97 and remained constant during the 9 months of therapy. The ARR baseline was 0.72 and dropped to 0.19 and 0.15 after 3 and 9 months, respectively. Despite a more than 4-fold higher ARR baseline, the treatment-naïve patients achieved an ARR at 9 months comparable with those previously treated. There were ten non-serious adverse reactions. After nine months of teriflunomide therapy, 63.3%, 21.2%, and 15.4% of patients had a high, medium, and low adherence, respectively, as per the MMAS-8; 100% of patients preferred an oral administration. The SEAMS score (odds ratio (OR) = 0.91; p = 0.013) and previous DMT (OR = 4.28; p = 0.005) were the only significant predictors of non-adherence. The disability, the quality of life, and beliefs about medicines had no measurable effect on adherence. Conclusion: After nine months of teriflunomide therapy, both the disability and quality of life remained stable; the relapse rate significantly decreased, 63.3% of patients had a high adherence, and 100% of patients preferred an oral administration. A low adherence was associated with previous DMT experiences and a low self-efficacy for the appropriate medication (i.e., the confidence in one’s ability to take medication correctly)