Zobrazeno 1 - 10
of 13
pro vyhledávání: '"David Pätzel"'
Publikováno v:
SN Computer Science. 3
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a2442e4743c4d6f8c48ae81b6f2f8b14
https://doi.org/10.1007/s42979-022-01352-1
https://doi.org/10.1007/s42979-022-01352-1
Publikováno v:
Metaheuristics for Machine Learning ISBN: 9789811938870
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ba050678b1b1594d46729ed8ed7a1471
https://doi.org/10.1007/978-981-19-3888-7_3
https://doi.org/10.1007/978-981-19-3888-7_3
Autor:
Michael Heider, Helena Stegherr, David Pätzel, Roman Sraj, Jonathan Wurth, Benedikt Volger, Jörg Hähner
To fill the increasing demand for explanations of decisions made by automated prediction systems, machine learning (ML) techniques that produce inherently transparent models are directly suited. Learning Classifier Systems (LCSs), a family of rule-ba
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b9ad6c81152848f6ac761ef8f5204fd6
https://opus.bibliothek.uni-augsburg.de/opus4/files/104138/104138.pdf
https://opus.bibliothek.uni-augsburg.de/opus4/files/104138/104138.pdf
Publikováno v:
GECCO Companion
The International Workshop on Learning Classifier Systems (IWLCS) is an annual workshop at the GECCO conference where new concepts and results regarding learning classifier systems (LCSs) are presented and discussed. One recurring part of the worksho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c8485bdb393a2fee40399e4506fa99e
https://doi.org/10.1145/3449726.3463173
https://doi.org/10.1145/3449726.3463173
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783030726980
EvoApplications
EvoApplications
With the rise of test automation, companies start to rely on large amounts of test cases. However, there are situations where it is unfeasible to perform every test case as only a limited amount of time is available. Under such circumstances a set of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13b085566d3083b7a867f2edf42676d8
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83082
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83082
Publikováno v:
Architecture of Computing Systems ISBN: 9783030816810
ARCS
ARCS
Testing is a vital part of the development of a new software product. With the rise of test automation, companies more and more rely on large sets of test cases. This leads to situations in which it is unfeasible to run all tests due to a limited tim
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f0c68445e8c76cd1a024bd4b27cdfc0
https://doi.org/10.1007/978-3-030-81682-7_9
https://doi.org/10.1007/978-3-030-81682-7_9
Publikováno v:
IJCCI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::049ed37a381701e5a7c35936467423b0
https://doi.org/10.5220/0010105700490058
https://doi.org/10.5220/0010105700490058
Publikováno v:
GECCO Companion
The International Workshop on Learning Classifier Systems (IWLCS) is a yearly workshop at the GECCO conference where new concepts and results all around Learning Classifier Systems (LCSs) are presented and discussed. One recurring part of the worksho
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb673e1404280806edc57f12a584ee8d
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83080
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83080
Publikováno v:
GECCO Companion
Testing is a crucial part in the development of new products. With the rise of test automation methods, companies start relying on an even higher number of tests. Sometimes it is not feasible to run all tests and the goal is to determine which tests
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::006e1dec51b82e6633820099eb2a30e6
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83050
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/83050
Publikováno v:
GECCO Companion
We present a first evaluation of a new accuracy-based Pittsburgh-style learning classifier system (LCS) for supervised learning of multi-dimensional continuous decision problems: The SupRB-1 (Supervised Rule-Based) learning system. Designed primarily
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36f3f9c189e2a4b9be35dba838fde945