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Collections :	Ιδρυματικό Αποθετήριο ΟΠΑ / AUEB Institutional Repository Σχολή Επιστημών και Τεχνολογίας της Πληροφορίας / School of Informatics Τμήμα Στατιστικής / Department of Statistics Μεταπτυχιακές Εργασίες / Postgraduate dissertations

Title :	Model based clustering for high dimensional data

Alternative Title :	Ομαδοποίηση με τη χρήση μοντέλων για δεδομένα μεγάλων διαστάσεων

Creator :	Paizi, Vassiliki

Contributor :	Karlis, Dimitrios (Επιβλέπων καθηγητής) Athens University of Economics and Business, Department of Statistics (Degree granting institution)

Type :	Text

Extent :	86 p.

Language :	en

Abstract :	The rapid increase in the size of data sets makes clustering all the more important to capture and summarize the information; at the same time clustering is more difficult to be accomplished. If model-based clustering is applied directly to a large data set, it is too slow for practical application. A simple and common approach is to first cluster a random sample of moderate size, and then use this clustering model in this way to classify the remainder of the objects.

Abstract :

The rapid increase in the size of data sets makes clustering all the more important to capture and summarize the information; at the same time clustering is more difficult to be accomplished. If model-based clustering is applied directly to a large data set, it is too slow for practical application. A simple and common approach is to first cluster a random sample of moderate size, and then use this clustering model in this way to classify the remainder of the objects.

Subject :	Model- based clustering Large data Factor analyzers

Date Issued :	30-06-2016

Licence :

File: Paizi_2016.pdf

Type: application/pdf

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