diplomsko delo
Žan Jonke (Author), Danijel Skočaj (Mentor), Martin Schüßler (Co-mentor)

Abstract

Veliko današnjih informacijskih sistemov uporablja v zalednem sistemu algoritme strojnega učenja, katerih rezultati so lahko težko razumljivi računski modeli, npr. umetne nevronske mreže. Eden izmed primerov uporabnosti teh modelov so sistemi za podporo odločanju, katerih cilj je, da ljudje z njihovo pomočjo pridejo do boljše odločitve. V tem delu raziščemo, kako lahko lokalne naknadne razlage vplivajo na odločanje uporabnikov in njihovo uporabnost v tovrstnih sistemih. V ta namen smo izvedli eksperiment z ljudmi, kjer smo v treh različnih sejah spremljali obnašanja uporabnikov in jih med seboj primerjali.

Keywords

interpretabilnost;LIME;konvolucijske nevronske mreže;računalništvo in informatika;univerzitetni študij;diplomske naloge;

Data

Language: Slovenian
Year of publishing:
Typology: 2.11 - Undergraduate Thesis
Organization: UL FRI - Faculty of Computer and Information Science
Publisher: [Ž. Jonke]
UDC: 004.85(043.2)
COBISS: 19155715 Link will open in a new window
Views: 1033
Downloads: 178
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Other data

Secondary language: English
Secondary title: Decision support system with explanations of artificial neural networks predictions
Secondary abstract: A lot of modern day applications use machine learning algorithms, which may produce computer models, that are hard to understand. These models are applicable in decision support systems, where they help users make better decisions. Here we investigate how can local post-hoc explanations affect user decisions and their overall utility. We have conducted experiments with people where we simulated three environments and monitored user behaviour in each of them, which we later analysed.
Secondary keywords: interpretability;LIME;convolutional neural networks;computer and information science;diploma;
Type (COBISS): Bachelor thesis/paper
Study programme: 1000468
Embargo end date (OpenAIRE): 1970-01-01
Thesis comment: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages: 49 str.
ID: 11811516