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Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study

Bernard, Jurgen ; Hutter, Marco ; Zeppelzauer, Matthias ; Fellner, Dieter ; Sedlmair, Michael (2018)
Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study.
In: IEEE Transactions on Visualization and Computer Graphics, 24 (1)
doi: 10.1109/TVCG.2017.2744818
Artikel, Bibliographie

Kurzbeschreibung (Abstract)

Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In this work, we conduct an experiment with three parts to assess and compare the performance of these different labeling strategies. In our study, we (1) identify different visual labeling strategies for user-centered labeling, (2) investigate strengths and weaknesses of labeling strategies for different labeling tasks and task complexities, and (3) shed light on the effect of using different visual encodings to guide the visual-interactive labeling process. We further compare labeling of single versus multiple instances at a time, and quantify the impact on efficiency. We systematically compare the performance of visual interactive labeling with that of active learning. Our main findings are that visual-interactive labeling can outperform active learning, given the condition that dimension reduction separates well the class distributions. Moreover, using dimension reduction in combination with additional visual encodings that expose the internal state of the learning model turns out to improve the performance of visual-interactive labeling.

Typ des Eintrags: Artikel
Erschienen: 2018
Autor(en): Bernard, Jurgen ; Hutter, Marco ; Zeppelzauer, Matthias ; Fellner, Dieter ; Sedlmair, Michael
Art des Eintrags: Bibliographie
Titel: Comparing Visual-Interactive Labeling with Active Learning: An Experimental Study
Sprache: Englisch
Publikationsjahr: 2018
Titel der Zeitschrift, Zeitung oder Schriftenreihe: IEEE Transactions on Visualization and Computer Graphics
Jahrgang/Volume einer Zeitschrift: 24
(Heft-)Nummer: 1
DOI: 10.1109/TVCG.2017.2744818
URL / URN: https://doi.org/10.1109/TVCG.2017.2744818
Kurzbeschreibung (Abstract):

Labeling data instances is an important task in machine learning and visual analytics. Both fields provide a broad set of labeling strategies, whereby machine learning (and in particular active learning) follows a rather model-centered approach and visual analytics employs rather user-centered approaches (visual-interactive labeling). Both approaches have individual strengths and weaknesses. In this work, we conduct an experiment with three parts to assess and compare the performance of these different labeling strategies. In our study, we (1) identify different visual labeling strategies for user-centered labeling, (2) investigate strengths and weaknesses of labeling strategies for different labeling tasks and task complexities, and (3) shed light on the effect of using different visual encodings to guide the visual-interactive labeling process. We further compare labeling of single versus multiple instances at a time, and quantify the impact on efficiency. We systematically compare the performance of visual interactive labeling with that of active learning. Our main findings are that visual-interactive labeling can outperform active learning, given the condition that dimension reduction separates well the class distributions. Moreover, using dimension reduction in combination with additional visual encodings that expose the internal state of the learning model turns out to improve the performance of visual-interactive labeling.

Freie Schlagworte: Labeling, Information visualization, Visual analytics, Active learning, Machine learning, Classifications
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Graphisch-Interaktive Systeme
Hinterlegungsdatum: 26 Jun 2019 07:43
Letzte Änderung: 04 Feb 2022 12:38
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