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Identifier 000450288
Title Comparative study of machine learning algorithms in economics's interest time series's data
Alternative Title Συγκριτική μελέτη αλγόριθμων μηχανικής μάθησης σε οικονομικού ενδιαφέροντος δεδομένα χρονολογικών σειρών
Author Αναγνωστάκης, Μιχαήλ
Thesis advisor Τσιώτας Γεώργιος
Reviewer Τζίνιους Μαργαρίτα
Τσαγρής Μιχαήλ
Abstract At the first part of this master thesis, initially we will explain neural net¬works and KNN, the theoretical background of applying k-nearest neighbor to time series forecasting. Afterwards we will make an application in monthly TOYOTA car sales (registrations) in Greece, data from AMVIR from Jan¬uary 2010 until and October 2021. We generate multiple KNN regression models, in order to make comparison. The simpler of them, with k=3, k=2, k=l, produce encouraging predictive results for our data set. In addition we generate an exponential smoothing model as a strict comparing basis for the kNN regression models.
Language English
Subject Forecasting
KNNregression
Machine learning
ΚΝΝ παλινδρόμηση
Μηχανική μάθηση
Προβλέψεις
Issue date 2022-06-20
Collection   School/Department--School of Social Sciences--Department of Economics--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/8/3/b/metadata-dlib-1661851150-93872-10277.tkl Bookmark and Share
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