Download presentation_PlatzerJuergen

Enhancing
Interactive Visual Data Analysis
by
Statistical Functionality
Jürgen Platzer
VRVis Research Center
Vienna, Austria
http://www.VRVis.at/
Overview
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Motivation
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Sample Application
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Statistics Library for Information
Visualization
Conclusions
Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Motivation
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Information visualization and statistical methods try to enable a
better insight into data
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The same goal is reached by different means
Information Visualization
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User’s pattern recognition system
Creates interactively modifiable
graphics
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Allows interactive efficient information
drill-down
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Low dimensional features are easily
detected and analyzed.
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Linked views allow interactive
investigation of functional coherences.
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Jürgen Platzer
Statistical Routines
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Today’s computational possibilities
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Based on the knowledgeable theory of data
exploration
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Considers multivariate relationships
Computation of facts, summaries, models, ...
A large variety of algorithms for specific
tasks (clustering, dimension reduction,...)
Results can be easily reproduced
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Aim of this work
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Put user’s input and algorithmic
capabilities on the same level.
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Let them interactively communicate
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Show that the interactive combination of
the strength of both fields makes visual
data mining more efficient.
Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Statistics Library for InfoViz
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Find the most important statistical
functions for explorative data analysis.
 Clustering (Hierarchical approaches, partitional
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heuristics)
Dimension reduction (MDS, PCA, SOM)
Transformation of Dimensions (Linear vs. nonlinear)
Statistical Moments (classic vs. robust)
Regression
Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Statistics Library for InfoViz
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Additionally include innovative concepts
 Robustness
 Reduce influence of outliers
 Detect outliers
 Integration of multivariate outlier identification
 Fuzzyness
 Data comes from real world
 The real world is not based on bits!-)
 Integrate uncertainty in clustering by fuzzy k
means
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Statistics Library for InfoViz
 Fuzzy k means (UVW dataset - 149 769 data items)
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Statistics Library for InfoViz
 Create hooks of interaction
 Allow the interactive communication between
algorithm and the user.
 Immediate updates of summaries based on
selections
 Translation of user action into parameter settings
 Starting algorithms based on previous results
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Sample Application
 Interactive Clustering (Letter image recognition
data – 4640 data items, 6 groups)
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Sample Application
 Interactive Clustering (Letter image recognition
data – 4640 data items, 6 groups)
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Sample Application
 Interactive Clustering (Letter image recognition
data – 4640 data items, 6 groups)
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Conclusions
 Keyword: INTERACTIVITY
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Immediate validation of results
Immediate adaptation of algorithms
Immediate numerical feedback of user actions
 Information exchange user / algorithm =
incorporation of multivariate features
 Research of possible communication concepts
between user and statistical algorithms
 Translation of user actions into parameter settings
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Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
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Acknowledgement
Peter Filzmoser
Helwig Hauser
Harald Piringer
Austrian research program Kplus
Jürgen Platzer
Enhancing Interactive Visual Data Analysis by Statistical Functionality
May 22, 2017
Thank you for your attention.
Are there any questions?
http://www.VRVis.at/