Scipediacontent: Scipediacontent moved page Draft Content 987997571 to Evans et al 2020a

2021-02-01T23:46:33Z

Scipediacontent moved page Draft Content 987997571 to Evans et al 2020a

Scipediacontent: Created page with " == Abstract == common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of thi..."

2021-02-01T23:46:28Z

Created page with " == Abstract == common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of thi..."

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== Abstract ==

common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of this is that there are still hyperparameters which must be tuned in order to achieve good performance. In this work, we propose a near "parameter-free" genetic programming approach, which adapts the hyperparameter values throughout evolution without ever needing to be specified manually. We apply this to the area of automated machine learning (by extending TPOT), to produce pipelines which can effectively be claimed to be free from human input, and show that the results are competitive with existing state-of-the-art which use hand-selected hyperparameter values. Pipelines begin with a randomly chosen estimator and evolve to competitive pipelines automatically. This work moves towards a truly automatic approach to AutoML.

Comment: 18 pages (single column), 2 figure

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/2001.10178 http://arxiv.org/abs/2001.10178]

* [http://arxiv.org/pdf/2001.10178 http://arxiv.org/pdf/2001.10178]

* [http://xplorestaging.ieee.org/ielx7/9178820/9185488/09185770.pdf?arnumber=9185770 http://xplorestaging.ieee.org/ielx7/9178820/9185488/09185770.pdf?arnumber=9185770],
: [http://dx.doi.org/10.1109/cec48606.2020.9185770 http://dx.doi.org/10.1109/cec48606.2020.9185770]

* [https://dblp.uni-trier.de/db/journals/corr/corr2001.html#abs-2001-10178 https://dblp.uni-trier.de/db/journals/corr/corr2001.html#abs-2001-10178],
: [https://academic.microsoft.com/#/detail/3083002018 https://academic.microsoft.com/#/detail/3083002018]

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Scipediacontent: Scipediacontent moved page Draft Content 987997571 to Evans et al 2020a

Scipediacontent: Created page with " == Abstract == common claim of evolutionary computation methods is that they can achieve good results without the need for human intervention. However, one criticism of thi..."