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Title:
NAIVNI BAYESOV KLASIFIKATOR
Authors:
ID
Bozhinova, Monika
(
Author
)
ID
Guid, Nikola
(
Mentor
)
More about this mentor...
ID
Strnad, Damjan
(
Comentor
)
Files:
UN_Bozhinova_Monika_2015.pdf
(1,56 MB)
MD5: F5299646617CA4F0C2E7B29080715AEB
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
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:
naivni Bayesov klasifikator
,
izbira atributov
,
klasifikacija dokumentov
Place of publishing:
[Maribor
Publisher:
M. Bozhinova
Year of publishing:
2015
PID:
20.500.12556/DKUM-47689-792e8191-755e-4b3c-1c93-caa064ef5cba
UDC:
004.434:004.8(043.2)
COBISS.SI-ID:
18903830
NUK URN:
URN:SI:UM:DK:N8KX30B6
Publication date in DKUM:
27.05.2015
Views:
2889
Downloads:
436
Metadata:
Categories:
KTFMB - FERI
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Secondary language
Language:
English
Title:
NAIVE BAYES CLASSIFIER
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.
Keywords:
naive Bayes classifier
,
feature selection
,
document classification
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