Generating custom classification datasets by targeting the instance space

Mario A. Muñoz; Kate Smith-Miles

doi:10.1145/3067695.3082532

Generating custom classification datasets by targeting the instance space

Mario A. Muñoz, Kate Smith-Miles

School of Mathematics

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

8 Citations (Scopus)

Abstract

While machine learning has evolved at a fast pace in the last decades, the testing procedure of new methods may be not keeping pace. It often relies on well-studied collections of classification datasets such as the UCI repository. However, a meta-Analysis through features has showed that most datasets from UCI are not suffciently challenging to expose unique weaknesses of algorithms. In this paper we present a method to generate datasets with continuous, binary and categorical attributes, through the fitting of a Gaussian Mixture Model and a set of generalized Bernoulli distributions. By targeting empty areas of the instance space, this method has the potential to generate datasets with more diverse feature values.i.

Original language	English
Title of host publication	Proceedings of the Genetic and Evolutionary Computation Conference Companion
Subtitle of host publication	2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Pages	1582-1588
Number of pages	7
ISBN (Electronic)	9781450349390
DOIs	https://doi.org/10.1145/3067695.3082532
Publication status	Published - 15 Jul 2017
Event	The Genetic and Evolutionary Computation Conference 2017 - Berlin, Germany Duration: 15 Jul 2017 → 19 Jul 2017 Conference number: 19th http://gecco-2017.sigevo.org/index.html/HomePage.html https://dl.acm.org/doi/proceedings/10.1145/3071178 (Proceedings)

Conference

Conference	The Genetic and Evolutionary Computation Conference 2017
Abbreviated title	GECCO 2017
Country/Territory	Germany
City	Berlin
Period	15/07/17 → 19/07/17
Other	A Recombination of the 26th International Conference on Genetic Algorithms (ICGA) and the 22nd Annual Genetic Programming Conference (GP). The Genetic and Evolutionary Computation Conference (GECCO) presents the latest high-quality results in genetic and evolutionary computation since 1999. Topics include: genetic algorithms,genetic programming, ant colony optimization and swarm intelligence, complex systems (artificiallife/robotics/evolvable hardware/generative and developmental systems/artificial immune systems), digital entertainment technologies and arts, evolutionary combinatorial optimization and metaheuristics, evolutionary machine learning, evolutionary multiobjective optimization, evolutionary numerical optimization, real world applications, search-based software engineering, theory and more.
Internet address	http://gecco-2017.sigevo.org/index.html/HomePage.html https://dl.acm.org/doi/proceedings/10.1145/3071178 (Proceedings)

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10.1145/3067695.3082532

Cite this

Muñoz, M. A., & Smith-Miles, K. (2017). Generating custom classification datasets by targeting the instance space. In Proceedings of the Genetic and Evolutionary Computation Conference Companion: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763 (pp. 1582-1588). Association for Computing Machinery (ACM). https://doi.org/10.1145/3067695.3082532

Muñoz, Mario A. ; Smith-Miles, Kate. / Generating custom classification datasets by targeting the instance space. Proceedings of the Genetic and Evolutionary Computation Conference Companion: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763. New York NY USA : Association for Computing Machinery (ACM), 2017. pp. 1582-1588

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Muñoz, MA & Smith-Miles, K 2017, Generating custom classification datasets by targeting the instance space. in Proceedings of the Genetic and Evolutionary Computation Conference Companion: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763. Association for Computing Machinery (ACM), New York NY USA, pp. 1582-1588, The Genetic and Evolutionary Computation Conference 2017, Berlin, Berlin, Germany, 15/07/17. https://doi.org/10.1145/3067695.3082532

Generating custom classification datasets by targeting the instance space. / Muñoz, Mario A.; Smith-Miles, Kate.
Proceedings of the Genetic and Evolutionary Computation Conference Companion: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763. New York NY USA: Association for Computing Machinery (ACM), 2017. p. 1582-1588.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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Muñoz MA, Smith-Miles K. Generating custom classification datasets by targeting the instance space. In Proceedings of the Genetic and Evolutionary Computation Conference Companion: 2017 Genetic and Evolutionary Computation Conference Companion, GECCO 2017; Berlin; Germany; 15 July 2017 through 19 July 2017; Code 128763. New York NY USA: Association for Computing Machinery (ACM). 2017. p. 1582-1588 doi: 10.1145/3067695.3082532

Generating custom classification datasets by targeting the instance space

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Stress-testing algorithms: generating new test instances to elicit insights

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Generating custom classification datasets by targeting the instance space

Abstract

Conference

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Stress-testing algorithms: generating new test instances to elicit insights

Cite this