Naslov
Comparative Analysis of Decision Tree Methods from Two Scientific Fields

Autori
Kadoić, Nikola ; Oreški, Dijana ; Lendl, Marija

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 16th International Symposium on Operational Research in Slovenia / Drobne, S., Zadnik Stirn, L., . Kljajic Borstnar, M., Povh, J., . Zerovnik, J - Online, 2021, 683-690

ISBN
978-961-6165-57-0

Skup
16th International Symposium on Operational Research (SOR 2021)

Mjesto i datum
Online, 22.09.2021. - 24.09.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
decision tree, decision making ; risk ; data mining ; machine learning ; uncertainty

Sažetak
There are two methods called a decision tree. One belongs to the field of decision making in uncertainty and risks (UR), and the other belongs to the field of data mining (DM). Researchers, practitioners, and students often mix those methods or think that there is only one method. There are several goals of this paper. The first goal is to present the basics of both methods in one place. The presentation is given in the paper by explaining the methods through their elements, procedures, and demonstrations on simple examples. The second goal is to give a comparison of the methods. The comparative analysis is implemented respecting several comparisons criteria and identifying the similarities and differences between the two methods. The third goal is to analyze and demonstrate the possibilities of combining the two methods. Since the UR decision tree can be observed as an extension of the DM decision tree, the natural combination of methods is that outputs of the DM decision tree are inputs for the UR decision tree. The paper contains a short demo example of how to combine those two methods.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA