Predikcia inflácie vybranými metódami strojového učenia v krajinách V4

Autor:	Číriová, Nora
Jazyk:	slovenština
Rok vydání:	2018
Předmět:	dolování dat krosvalidace inflační faktory databáze cenová hladina harmonizovaný index spotřebitelských cen měnový vývoj národní banka data inflace
Druh dokumentu:	masterThesis
Popis:	The thesis analyzes the accuracy of the multi-step inflation forecast using se-lected methods of machine learning through inflationary factors in the Visegrad group countries. The methods that were applied in the work analysis are the re-gression of tree methods and the algorithm method to the k-nearest neighbors. Based on the regression tree method, we are able to identify factors that are most prominent in price level development. The output of the analysis consists of 8 models, the suitability and accuracy of which are discussed. The results of the em-pirical analysis are compared with the assumptions that were presented before the analysis has begun. This suggests that methods are not suitable for multi-step inflation prediction.
Databáze:	Networked Digital Library of Theses & Dissertations
Externí odkaz:	http://www.nusl.cz/ntk/nusl-429374 Zobrazit plný text záznamu