Eurographics/ Ieee-vgtc Symposium on Visualization 2010 Hypermoval: Interactive Visual Validation of Regression Models for Real-time Simulation

During the development of car engines, regression models that are based on machine learning techniques are increasingly important for tasks which require a prediction of results in real‐time. While the validation of a model is a key part of its identification process, existing computation‐ or visualization‐based techniques do not adequately support all aspects of model validation. The main contribution of this paper is an interactive approach called HyperMoVal that is designed to support multiple tasks related to model validation: 1) comparing known and predicted results, 2) analyzing regions with a bad fit, 3) assessing the physical plausibility of models also outside regions covered by validation data, and 4) comparing multiple models. The key idea is to visually relate one or more n‐dimensional scalar functions to known validation data within a combined visualization. HyperMoVal lays out multiple 2D and 3D sub‐projections of the n‐dimensional function space around a focal point. We describe how linking HyperMoVal to other views further extends the possibilities for model validation. Based on this integration, we discuss steps towards supporting the entire workflow of identifying regression models. An evaluation illustrates a typical workflow in the application context of car‐engine design and reports general feedback of domain experts and users of our approach. These results indicate that our approach significantly accelerates the identification of regression models and increases the confidence in the overall engineering process.

[1]  Matthew O. Ward,et al.  Model space visualization for multivariate linear trend discovery , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[2]  Sang-Cheol Seok,et al.  Using projection and 2D plots to visually reveal genetic mechanisms of complex human disorders , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[3]  Steven K. Feiner,et al.  Worlds within worlds: metaphors for exploring n-dimensional virtual worlds , 1990, UIST '90.

[4]  Ross T. Whitaker,et al.  Particle-based Sampling and Meshing of Surfaces in Multimaterial Volumes , 2008, IEEE Transactions on Visualization and Computer Graphics.

[5]  Ben Shneiderman,et al.  Visual information seeking: tight coupling of dynamic query filters with starfield displays , 1994, CHI '94.

[6]  Alfred Inselberg,et al.  The plane with parallel coordinates , 1985, The Visual Computer.

[7]  Ulrich Dohle,et al.  Pkw-Common-Rail-Systeme für künftige Emissionsanforderungen , 2005 .

[8]  Ken Brodlie,et al.  Visualizing and Investigating Multidimensional Functions , 2002, VisSym.

[9]  Wolfgang Berger,et al.  Quantifying and Comparing Features in High-Dimensional Datasets , 2008, 2008 12th International Conference Information Visualisation.

[10]  Denis Gracanin,et al.  Interactive visual analysis and exploration of injection systems simulations , 2005, VIS 05. IEEE Visualization, 2005..

[11]  Robert Spence,et al.  Externalising abstract mathematical models , 1996, CHI '96.

[12]  Ted Mihalisin,et al.  Visualizing multivariate functions, data, and distributions , 1991, IEEE Computer Graphics and Applications.

[13]  Chris Weaver,et al.  Conjunctive Visual Forms , 2009, IEEE Transactions on Visualization and Computer Graphics.

[14]  David Borland,et al.  Rainbow Color Map (Still) Considered Harmful , 2007, IEEE Computer Graphics and Applications.

[15]  Chris North,et al.  A radial focus+context visualization for multi-dimensional functions , 2002, IEEE Visualization, 2002. VIS 2002..

[16]  Ronald D. Snee,et al.  Validation of Regression Models: Methods and Examples , 1977 .

[17]  Jack P. C. Kleijnen,et al.  EUROPEAN JOURNAL OF OPERATIONAL , 1992 .

[18]  William S. Cleveland,et al.  Visualizing Data , 1993 .

[19]  Pierre Dragicevic,et al.  Rolling the Dice: Multidimensional Visual Exploration using Scatterplot Matrix Navigation , 2008, IEEE Transactions on Visualization and Computer Graphics.

[20]  Ben Shneiderman,et al.  Visual information seeking: tight coupling of dynamic query filters with starfield displays , 1994, CHI Conference Companion.

[21]  Tamara Munzner,et al.  A Nested Model for Visualization Design and Validation , 2009, IEEE Transactions on Visualization and Computer Graphics.

[22]  J. V. van Wijk,et al.  HyperSlice: visualization of scalar functions of many variables , 1993, VIS '93.

[23]  Jarke J. van Wijk,et al.  HyperSlice - Visualization of Scalar Functions of Many Variables , 1993, IEEE Visualization.

[24]  Urska Cvek,et al.  High-Dimensional Visualizations , 2002 .

[25]  Jürgen Hammer,et al.  Passenger car common rail systems for future emissions standards , 2005 .

[26]  Klaus Mueller,et al.  ClusterSculptor: A Visual Analytics Tool for High-Dimensional Data , 2007, 2007 IEEE Symposium on Visual Analytics Science and Technology.

[27]  Wolfgang Berger,et al.  A Multi-Threading Architecture to Support Interactive Visual Exploration , 2009, IEEE Transactions on Visualization and Computer Graphics.