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Possibilities of Using Statistical Methods in Insurance
Paugschová, Melinda ; Hanusek, Lubomír (advisor) ; Zichová, Jitka (referee)
Nazev prace: Moznosti vyu/iti statistickyeh metod v pojisYovnictvi Autor: Melinda Pnugschova Katedra: Katedra pravdepodobnosli a matematickestatistiky Vedouci diplomove pracc: Ing. Lubomir Ilanusek e-mail vedouciho: Lubomir.Hanusek@adastracorp.com Abstrakt: Tato diplomova prace se zabyva vybranymi stalistickymi mctodami vyuzivanymi v pojist'ovnictvi. Vyznamna cast pracc popisuje zaklady linearni regrcse, logistickc rcgrcse, diskriminacni analyzy, kontingenenich tabulek a klasifikaenich stromu. Ve zbytku prace se venujeme pouziti techto mctod v oblasti stanovovani pojistnych sazeb, marketingu a pojist- nych podvodu. V kapitole Pojistne sazby nastinujeme mo/nost jcjich stanoveni pouzitim kombinace modclfi linearni a logistickc rcgresc. Kapitola Marketing se zamehije na cilcni marketingovych kampani s vyuzitim diskriminacni analyzy, kontingencnich tabulek a klasi- fikacnfch stromu. V poslcdni kapitole pracc sc snazime upo/ornit na problem pojistnych podvodu v soLicasnosli a na dulezitost vytvafeni rnodelu pou/.ivanych k jejich dctekci. A- plikace mctod ilustrujcme na realnych a modelovych datech. K vypoctum pouzivame stati- sticky software R, v kapitole o marketingu software SPSS. KliCova slova: klasifikacni slromy, pojistnc sazby, cileny marketing, pojistny podvod Title: The options of using statistical...
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Possibilities of Using Statistical Methods in Insurance
Paugschová, Melinda ; Zichová, Jitka (referee) ; Hanusek, Lubomír (advisor)
Nazev prace: Moznosti vyu/iti statistickyeh metod v pojisYovnictvi Autor: Melinda Pnugschova Katedra: Katedra pravdepodobnosli a matematickestatistiky Vedouci diplomove pracc: Ing. Lubomir Ilanusek e-mail vedouciho: Lubomir.Hanusek@adastracorp.com Abstrakt: Tato diplomova prace se zabyva vybranymi stalistickymi mctodami vyuzivanymi v pojist'ovnictvi. Vyznamna cast pracc popisuje zaklady linearni regrcse, logistickc rcgrcse, diskriminacni analyzy, kontingenenich tabulek a klasifikaenich stromu. Ve zbytku prace se venujeme pouziti techto mctod v oblasti stanovovani pojistnych sazeb, marketingu a pojist- nych podvodu. V kapitole Pojistne sazby nastinujeme mo/nost jcjich stanoveni pouzitim kombinace modclfi linearni a logistickc rcgresc. Kapitola Marketing se zamehije na cilcni marketingovych kampani s vyuzitim diskriminacni analyzy, kontingencnich tabulek a klasi- fikacnfch stromu. V poslcdni kapitole pracc sc snazime upo/ornit na problem pojistnych podvodu v soLicasnosli a na dulezitost vytvafeni rnodelu pou/.ivanych k jejich dctekci. A- plikace mctod ilustrujcme na realnych a modelovych datech. K vypoctum pouzivame stati- sticky software R, v kapitole o marketingu software SPSS. KliCova slova: klasifikacni slromy, pojistnc sazby, cileny marketing, pojistny podvod Title: The options of using statistical...
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Quality measures of classification models and their conversion
Hanusek, Lubomír ; Hebák, Petr (advisor) ; Řezanková, Hana (referee) ; Skalská, Hana (referee)
Predictive power of classification models can be evaluated by various measures. The most popular measures in data mining (DM) are Gini coefficient, Kolmogorov-Smirnov statistic and lift. These measures are each based on a completely different way of calculation. If an analyst is used to one of these measures it can be difficult for him to asses the predictive power of a model evaluated by another measure. The aim of this thesis is to develop a method how to convert one performance measure into another. Even though this thesis focuses mainly on the above-mentioned measures, it deals also with other measures like sensitivity, specificity, total accuracy and area under ROC curve. During development of DM models you may need to work with a sample that is stratified by values of the target variable Y instead of working with the whole population containing millions of observations. If you evaluate a model developed on a stratified data you may need to convert these measures to the whole population. This thesis describes a way, how to carry out this conversion. A software application (CPM) enabling all these conversions makes part of this thesis. With this application you can not only convert one performance measure to another, but you can also convert measures calculated on a stratified sample to the whole population. Besides the above mentioned performance measures (sensitivity, specificity, total accuracy, Gini coefficient, Kolmogorov-Smirnov statistic), CPM will also generate confusion matrix and performance charts (lift chart, gains chart, ROC chart and KS chart). This thesis comprises the user manual to this application as well as the web address where the application can be downloaded. The theory described in this thesis was verified on the real data.
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