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Title:
Napovedovanje rezultatov rehabilitacije
Authors:
ID
Jančar, Jakob
(
Author
)
ID
Rajkovič, Uroš
(
Mentor
)
More about this mentor...
Files:
VS_Jancar_Jakob_2017.pdf
(2,58 MB)
MD5: 4974E394D2559EE6D9C618EDACA8FC28
PID:
20.500.12556/dkum/5237c9a9-0468-4470-83b5-5147525ea678
Language:
Slovenian
Work type:
Bachelor thesis/paper
Organization:
FOV - Faculty of Organizational Sciences in Kranj
Abstract:
Pridobili smo datoteko z izbranimi podatki o pacientih in pacientkah, ki so doživeli srčni infarkt. Zanimalo nas je, kateri parametri nam lahko pomagajo napovedati uspešnost rehabilitacije po srčnem infarktu. Proces podatkovnega rudarjenja je bil izveden z uporabo programa Orange. Uporabljene metode podatkovnega rudarjenja so bile Bayesov algoritem, CN2 inducirana pravila in odločitvena drevesa. Z uporabo teh metod je bil zgrajen model, ki omogoča testiranje vsake izmed metod, kar služi primerjavi metod. Za posamezno metodo so bile izbrane ustrezne funkcije vizualizacije, ki predstavijo odločitveno znanje. Naloga obravnava dva izmed možnih kriterijev za uspešno rehabilitacijo. Za vsakega izmed obeh primerov je podana primerjava rezultatov uporabljenih metod.
Keywords:
• Podatkovno rudarjenje • Srčni infarkt • Proces rehabilitacije
Place of publishing:
Maribor
Year of publishing:
2017
PID:
20.500.12556/DKUM-69046
COBISS.SI-ID:
7985427
NUK URN:
URN:SI:UM:DK:E6NHDWFY
Publication date in DKUM:
21.12.2017
Views:
1414
Downloads:
117
Metadata:
Categories:
FOV
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Licences
License:
CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:
http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:
The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:
23.11.2017
Secondary language
Language:
English
Title:
Predicting rehabilitation results
Abstract:
We have obtained a database with the selected information about male and female patients who survived a heart attack. We wanted to know which parameters can help us predict the success of the rehabilitation after the heart attack. The process of data mining was carried out using the Orange program. The used data mining methods were: Bayes algorithm, CN2 rule induction and decision trees. With the use of these methods we built a model that enabled testing of each of the methods. It served as a comparison of the methods. For each method, appropriate visualization features were selected in order to present decision-making knowledge. The task addresses two of the possible criteria for the successful rehabilitation. For each of these two cases we gave a comparison of the results of the used methods.
Keywords:
• Data mining • Heart attack • Rehabilitation process
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