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    Integrating Predictions in Time Series Model Selection (Unknown language)

    In: EuroVis Workshop on Visual Analytics (EuroVA) ; 73-77  ; 2015

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    Time series appear in many different domains. The main goal in time series analysis is to find a model for given time series. The selection of time series models is done iteratively based, usually, on information criteria and residual plots. These sources may show only small variations and, therefore, it is necessary to consider the prediction capabilities in the model selection process. When applying the model and including the prediction in an interactive visual interface it is still difficult to compare deviations from actual values or benchmark models. Judging which model fits the time series adequately is not well supported in current methods. We propose to combine visual and analytical methods to integrate the prediction capabilities in the model selection process and assist in the decision for an adequate and parsimonious model. In our approach a visual interactive interface is used to select and adjust time series models, utilize the prediction capabilities of models, and compare the prediction of multiple models in relation to the actual values.

    Table of contents conference proceedings

    The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.

    1
    Supporting Historical Research Through User-Centered Visual Analytics
    Boukhelifa, Nadia / Giannisakis, Emmanouil / Dimara, Evanthia / Willett, Wesley / Fekete, Jean-Daniel et al. | 2015
    7
    Inspector Gadget: Integrating Data Preprocessing and Orchestration in the Visual Analysis Loop
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    13
    Visual Scaffolding in Integrated Spatial and Nonspatial Analysis
    Marai, G. Elisabeta et al. | 2015
    19
    Interactive Image Feature Selection Aided by Dimensionality Reduction
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    25
    The Use of High-Dimensional Visualizations in Explaining Hospital Pricing Patterns
    Perkins, Miriam / Grinstein, Georges et al. | 2015
    31
    Attribute-based Visual Explanation of Multidimensional Projections
    Silva, Renato R. O. da / Rauber, Paulo E. / Martins, Rafael M. / Minghim, Rosane / Telea, Alexandru C. et al. | 2015
    37
    Visual-Interactive Text Analysis to Support Political Decision Making - From Sentiments to Arguments to Policies
    Ruppert, Tobias / Bernard, Jürgen / Lücke-Tieke, Hendrik / May, Thorsten / Kohlhammer, Jörn et al. | 2015
    43
    Trajectory-based Visual Analytics for Anomalous Human Movement Analysis using Social Media
    Chae, Junghoon / Cui, Yuchen / Jang, Yun / Wang, Guizhen / Malik, Abish / Ebert, David S. et al. | 2015
    49
    Integrated Spatial Uncertainty Visualization using Off-screen Aggregation
    Jäckle, Dominik / Senaratne, Hansi / Buchmüller, Juri / Keim, Daniel A. et al. | 2015
    55
    Visual Analytics and Uncertainty: Its Not About the Data
    MacEachren, Alan M. et al. | 2015
    61
    Visual Analysis of Relations in Attributed Time-Series Data
    Steiger, Martin / Bernard, Jürgen / Schader, Philipp / Kohlhammer, Jörn et al. | 2015
    67
    Exploration and Assessment of Event Data
    Bodesinsky, Peter / Alsallakh, Bilal / Gschwandtner, Theresia / Miksch, Silvia et al. | 2015
    73
    Integrating Predictions in Time Series Model Selection
    Bögl, Markus / Aigner, Wolfgang / Filzmoser, Peter / Gschwandtner, Theresia / Lammarsch, Tim / Miksch, Silvia / Rind, Alexander et al. | 2015
    79
    Gnaeus: Utilizing Clinical Guidelines for Knowledge-assisted Visualisation of EHR Cohorts
    Federico, Paolo / Unger, Jürgen / Amor-Amorós, Albert / Sacchi, Lucia / Klimov, Denis / Miksch, Silvia et al. | 2015

    How to get this title?

    Check access
    Download
    Commercial Copyright fee: €14.50 Basic fee: €4.00 Total price: €18.50
    Academic Copyright fee: €4.50 Basic fee: €2.00 Total price: €6.50

    Export, share and cite

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