ML Anthology

Framework for Exploring and Understanding Multivariate Correlations

Louis Kirsch, Niklas Riekenbrauck, Daniel Thevessen, Marcus Pappik, Axel Stebner, Julius Kunze, Alexander Meissner, Arvind Kumar Shekar, Emmanuel Müller
ECML-PKDD 2017 pp. 404-408
doi:10.1007/978-3-319-71273-4_40 /ecmlpkdd/2017/kirsch2017ecmlpkdd-framework/

Abstract

Feature selection is an essential step to identify relevant and non-redundant features for target class prediction. In this context, the number of feature combinations grows exponentially with the dimension of the feature space. This hinders the user’s understanding of the feature-target relevance and feature-feature redundancy. We propose an interactive Framework for Exploring and Understanding Multivariate Correlations (FEXUM), which embeds these correlations using a force-directed graph. In contrast to existing work, our framework allows the user to explore the correlated feature space and guides in understanding multivariate correlations through interactive visualizations.

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Cite

Text

Kirsch et al. "Framework for Exploring and Understanding Multivariate Correlations." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2017. doi:10.1007/978-3-319-71273-4_40

Markdown

[Kirsch et al. "Framework for Exploring and Understanding Multivariate Correlations." European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2017.](https://mlanthology.org/ecmlpkdd/2017/kirsch2017ecmlpkdd-framework/) doi:10.1007/978-3-319-71273-4_40

BibTeX

@inproceedings{kirsch2017ecmlpkdd-framework,
  title     = {{Framework for Exploring and Understanding Multivariate Correlations}},
  author    = {Kirsch, Louis and Riekenbrauck, Niklas and Thevessen, Daniel and Pappik, Marcus and Stebner, Axel and Kunze, Julius and Meissner, Alexander and Shekar, Arvind Kumar and Müller, Emmanuel},
  booktitle = {European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases},
  year      = {2017},
  pages     = {404-408},
  doi       = {10.1007/978-3-319-71273-4_40},
  url       = {https://mlanthology.org/ecmlpkdd/2017/kirsch2017ecmlpkdd-framework/}
}