diplomsko delo
Nace Kovačič (Author), Blaž Zupan (Mentor)

Abstract

V diplomskem delu predstavimo pristop k napovedovanju dogodkov drastičnih sprememb valutnega tečaja kriptovalut. Za napovedovanje uporabimo modela XGBClassifier in konvolucijsko nevronsko mrežo. Primerjamo njuno točnost napovedi in spremembo točnosti napovedi pri napovedovanju z možnostjo zavrnitve.

Keywords

časovne vrste;časovne vrste z zavrnitvijo;konvolucijske nevronske mreže;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: [N. Kovačič]
UDC: 004.8(043.2)
COBISS: 169130755 Link will open in a new window
Views: 49
Downloads: 6
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Other data

Secondary language: English
Secondary title: Time Series with Classification and Rejection
Secondary abstract: In this thesis we present an approach to predicting events of drastic changes in the exchange rate of cryptocurrencies. For prediction we use the XGBClassifier model and the convolutional neural network. We compare their prediction accuracy and the change in prediction accuracy when predicting with the option of rejection.
Secondary keywords: timeseries;timeseries with rejection;convolutional neural networks;computer science;diploma;Računalništvo;Univerzitetna in visokošolska dela;
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: 35 str.
ID: 21439492