diplomsko delo
Monika Bozhinova (Author), Nikola Guid (Mentor), Damjan Strnad (Co-mentor)

Abstract

V sodobnem času je samodejna klasifikacija dokumentov postala pomembna raziskovalna tema. V diplomskem delu smo teoretično razložili izpeljavo in uporabo naivnega Bayesovega klasifikatorja in opisali dva dogodkovna modela naivnega Bayesovega klasifikatorja ter večje število metod izbire atributov. Glavni del diplomskega dela je sestavljen iz opisa naše interaktivne programske rešitve za klasifikacijo dokumentov z uporabo opisanih dogodkovnih modelov in metod, eksperimentalnih rezultatov, pridobljenih s pomočjo naše aplikacije, in empirične primerjave med kombinacijami zasnovanih dogodkovnih modelov naivnega Bayesovega klasifikatorja in metod izbire atributov.

Keywords

klasifikacija dokumentov;naivni Bayesov klasifikator;izbira atributov;dogodkovni modeli;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher: M. Bozhinova
UDC: 004.434:004.8(043.2)
COBISS: 18903830 Link will open in a new window
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Other data

Secondary language: English
Secondary title: NAIVE BAYES CLASSIFIER
Secondary abstract: Nowadays, the automatic classification of documents has become an important research topic. In this thesis, we theoretically explain the derivation and usage of the naive Bayes classifier and describe two event models of naive Bayes classifier and several feature selection methods. The main part of this thesis consists of a description of the implemented interactive application for document classification using the described event models and methods, the experimental results obtained from the application, and an empirical comparison among the combinations of the implemented event models of naive Bayes classifier and feature selection methods.
Secondary keywords: naive Bayes classifier;feature selection;document classification;
URN: URN:SI:UM:
Type (COBISS): Bachelor thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije
Pages: VII, 28 f.
ID: 8739335