Logo des Repositoriums
 

DICE: Density-based Interactive Clustering and Exploration

dc.contributor.authorKazempour, Daniyal
dc.contributor.authorKazakov, Maksim
dc.contributor.authorKröger, Peer
dc.contributor.authorSeidl, Thomas
dc.contributor.editorGrust, Torsten
dc.contributor.editorNaumann, Felix
dc.contributor.editorBöhm, Alexander
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorHärder, Theo
dc.contributor.editorRahm, Erhard
dc.contributor.editorHeuer, Andreas
dc.contributor.editorKlettke, Meike
dc.contributor.editorMeyer, Holger
dc.date.accessioned2019-04-11T07:21:34Z
dc.date.available2019-04-11T07:21:34Z
dc.date.issued2019
dc.description.abstractClustering algorithms are mostly following the pipeline to provide input data, and hyperparameter values. Then the algorithms are executed and the output files are generated or visualized. We provide in our work an early prototype of an interactive density-based clustering tool named DICE in which the users can change the hyperparameter settings and immediately observe the resulting clusters. Further the users can browse through each of the single detected clusters and get statistics regarding as well as a convex hull profile for each cluster. Further DICE keeps track of the chosen settings, enabling the user to review which hyperparameter values have been previously chosen. DICE can not only be used in scientific context of analyzing data, but also in didactic settings in which students can learn in an exploratory fashion how a density-based clustering algorithm like e.g. DBSCAN behaves.en
dc.identifier.doi10.18420/btw2019-42
dc.identifier.isbn978-3-88579-683-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/21729
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofBTW 2019
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) – Proceedings, Volume P-289
dc.subjectDensity-based clustering
dc.subjectInteractive
dc.subjectExploration
dc.subjectHyperparameters
dc.titleDICE: Density-based Interactive Clustering and Explorationen
gi.citation.endPage550
gi.citation.startPage547
gi.conference.date4.-8. März 2019
gi.conference.locationRostock
gi.conference.sessiontitleDemonstrationen

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
E12-1.pdf
Größe:
463.18 KB
Format:
Adobe Portable Document Format