"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction

André Artelt, André Artelt, Alexander Schulz, Barbara Hammer

2023

Abstract

Dimensionality reduction is a popular preprocessing and a widely used tool in data mining. Transparency, which is usually achieved by means of explanations, is nowadays a widely accepted and crucial requirement of machine learning based systems like classifiers and recommender systems. However, transparency of dimensionality reduction and other data mining tools have not been considered much yet, still it is crucial to understand their behavior – in particular practitioners might want to understand why a specific sample got mapped to a specific location. In order to (locally) understand the behavior of a given dimensionality reduction method, we introduce the abstract concept of contrasting explanations for dimensionality reduction, and apply a realization of this concept to the specific application of explaining two dimensional data visualization.

Paper Citation

in Harvard Style

Artelt A., Schulz A. and Hammer B. (2023). "Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-626-2, pages 27-38. DOI: 10.5220/0011618300003411

in Bibtex Style

@conference{icpram23,
author={André Artelt and Alexander Schulz and Barbara Hammer},
title={"Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction},
booktitle={Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2023},
pages={27-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011618300003411},
isbn={978-989-758-626-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - "Why Here and not There?": Diverse Contrasting Explanations of Dimensionality Reduction
SN - 978-989-758-626-2
AU - Artelt A.
AU - Schulz A.
AU - Hammer B.
PY - 2023
SP - 27
EP - 38
DO - 10.5220/0011618300003411