Return to search

Klasifikavimo su mokytoju metodų lyginamoji analizė / A comparative analysis of supervised classification methods

Supervised classification methods are applied in many fields. The main problem of applying these methods is how to select the most appropriate method in particular case. The literary review was fulfilled and the advantages and disadvantages of mostly used criterion of supervised classification methods comparisons were ascertained. Then the methodology of comparisons was suggested. The analysis of SAS system procedures and macro commands was made. It was ascertained that there is not comfortable software which allows comparing the results of supervised classification methods. This work demands a lot of work, good knowledge of SAS programming language and high qualification in programming. So, the main purpose of this work is to expand the statistical data analysis system SAS possibilities in comparison of supervised classification methods and classificate various data.
In this work the possibilities of SAS system are expanded by the tool which allows comparing quality of the linear, quadratic, kernel, nearest neighbor’s discriminant analysis and logistic regression analysis methods. There were used classification error estimates which were got by resubstition, cross–validation leave one out, bootstrap and Monte Carl cross–validation methods, although classification error confidence intervals which were got by non-parametric bootstrap method. The test of created tool was made with various data (different sample sizes, various classis separability, violations of assumptions... [to full text]

Identiferoai:union.ndltd.org:LABT_ETD/oai:elaba.lt:LT-eLABa-0001:E.02~2006~D_20060605_092832-93331
Date05 June 2006
CreatorsŠimkevičius, Simonas
ContributorsJanilionis, Vytautas, Saulis, Leonas, Aksomaitis, Algimantas, Šaferis, Viktoras, Barauskas, Arūnas, Valakevičius, Eimutis, Navickas, Zenonas, Rudzkis, Rimantas, Pekarskas, Vidmantas, Kaunas University of Technology
PublisherLithuanian Academic Libraries Network (LABT), Kaunas University of Technology
Source SetsLithuanian ETD submission system
LanguageLithuanian
Detected LanguageEnglish
TypeMaster thesis
Formatapplication/pdf
Sourcehttp://vddb.library.lt/obj/LT-eLABa-0001:E.02~2006~D_20060605_092832-93331
RightsUnrestricted

Page generated in 0.002 seconds