loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Fabian Bürger and Josef Pauli

Affiliation: University of Duisburg-Essen, Germany

ISBN: 978-989-758-173-1

Keyword(s): Model Selection, Representation Learning, Classification, Evolutionary Optimization.

Related Ontology Subjects/Areas/Topics: Combinatorial Optimization ; Embedding and Manifold Learning ; Evolutionary Computation ; Feature Selection and Extraction ; Model Selection ; Pattern Recognition ; Theory and Methods

Abstract: The development of classification systems that meet the desired accuracy levels for real world-tasks applications requires a lot of expertise. Numerous challenges, like noisy feature data, suboptimal algorithms and hyperparameters, degrade the generalization performance. On the other hand, almost countless solutions have been developed, e.g. feature selection, feature preprocessing, automatic algorithm and hyperparameter selection. Furthermore, representation learning is emerging to automatically learn better features. The challenge of finding a suitable and tuned algorithm combination for each learning task can be solved by automatic optimization frameworks. However, the more components are optimized simultaneously, the more complex their interplay becomes with respect to the generalization performance and optimization run time. This paper analyzes the interplay of the components in a holistic framework which optimizes the feature subset, feature preprocessing, representation learnin g, classifiers and all hyperparameters. The evaluation on a real-world dataset that suffers from the curse of dimensionality shows the potential benefits and risks of such holistic optimization frameworks. (More)

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.209.80.87

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Bürger, F. and Pauli, J. (2016). Understanding the Interplay of Simultaneous Model Selection and Representation Optimization for Classification Tasks.In Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-173-1, pages 283-290. DOI: 10.5220/0005705302830290

@conference{icpram16,
author={Fabian Bürger. and Josef Pauli.},
title={Understanding the Interplay of Simultaneous Model Selection and Representation Optimization for Classification Tasks},
booktitle={Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2016},
pages={283-290},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005705302830290},
isbn={978-989-758-173-1},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Understanding the Interplay of Simultaneous Model Selection and Representation Optimization for Classification Tasks
SN - 978-989-758-173-1
AU - Bürger, F.
AU - Pauli, J.
PY - 2016
SP - 283
EP - 290
DO - 10.5220/0005705302830290

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.