Interpretacija odločitev nevronske mreže z metodo lime : diplomsko delo

Dajčman, Kristijan

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Title:	Interpretacija odločitev nevronske mreže z metodo lime : diplomsko delo
Authors:	ID Dajčman, Kristijan (Author) ID Strnad, Damjan (Mentor) More about this mentor... ID Borovič, Mladen (Comentor)
Files:	UN_Dajcman_Kristijan_2023.pdf (2,88 MB) MD5: 3AF0C83C4A174D077D76D81B1599EEFE
Language:	Slovenian
Work type:	Bachelor thesis/paper
Typology:	2.11 - Undergraduate Thesis
Organization:	FERI - Faculty of Electrical Engineering and Computer Science
Abstract:	V diplomskem delu interpretiramo odločitve globokih nevronskih mrež za analizo sentimenta slovenskih in angleških besedil z metodo LIME. Nevronske mreže veljajo za črne škatle, saj je težko pojasniti njihove odločitve s samimi utežmi, kar predstavlja težave pri posvojitvi takšnih modelov v situacijah, kjer je pomembna transparentnost in zanesljivost odločitev. Problem črnih škatel lahko rešimo z metodami interpretiranja, kot je LIME, ki pojasni odločitev črne škatle z lokalnim nadomestkom. V tem delu interpretiramo napovedi treh nevronskih mrež z metodo LIME in poskušamo na podlagi interpretacij razložiti delovanje nevronskih mrež.
Keywords:	LIME, razložljiva umetna inteligenca, nevronska mreža, analiza sentimenta
Place of publishing:	Maribor
Place of performance:	Maribor
Publisher:	[K. Dajčman]
Year of publishing:	2023
Number of pages:	1 spletni vir (1 datoteka PDF (XIII, 46 f.))
PID:	20.500.12556/DKUM-84914
UDC:	004.8(043.2)
COBISS.SI-ID:	169212931
Publication date in DKUM:	21.09.2023
Views:	561
Downloads:	70
Metadata:
Categories:	KTFMB - FERI
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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:	08.08.2023

Secondary language

Language:	English
Title:	Interpretation of neural network decisions using the lime method
Abstract:	In this thesis, we interpret the decisions of deep neural networks for sentiment analysis of Slovenian and English texts using the LIME method. Neural networks are considered black boxes because it is difficult to explain their decisions based solely on the weights, which poses challenges for adopting such models in situations where transparency and reliability of decisions are important. The problem of black boxes can be addressed with interpretation methods such as LIME, which explains the decision of a black box with a local surrogate. In this work, we interpret the predictions of three neural networks using the LIME method and attempt to explain the functioning of neural networks based on these interpretations.
Keywords:	LIME, interpretable artificial intelligence, neural network, sentiment analysis

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