Intrinsische Dimension und Knoteneinbettungen

Published by stubbemann on

Intrinsische Dimension und Knoteneinbettungen

In dieser Arbeit soll untersucht werden, wie hoch die intrinsische Dimension von Datensätzen ist, welche mit verschiedenen Knoteneinbettungsverfahren aus Graphen erstellt wurden.

Informationen: Maximilian Stubbemann

Categories: AllgemeinBachelorarbeitMasterarbeitMethodischer Schwerpunkt
Tags:

Related Posts

Allgemein

Temporal Ordinal Motifs in Topic Models

Temporal Ordinal Motifs in Topic Models Topic models are, often, dimension reduction techniques for large corpora of textual documents. A central aspect to these models is that they allow for text based explanations of the Read more…

Allgemein

Ordinal Motifs in Hierarchical Topic Models

Ordinal Motifs in Hierarchical Topic Models Topic models are, often, dimension reduction techniques for large corpora of textual documents. A central aspect to these models is that they allow for text based explanations of the Read more…

Allgemein

Network Motifs in Topic Flow Networks

Network Motifs in Topic Flow Networks In scientometrics, scientific collaboration is often analyzed by means of co-authorships. An aspect which is often overlooked and more difficult to quantify is the flow of expertise between authors Read more…