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Data Selection for Neural Networks

Publication date: 24.03.2017

Schedae Informaticae, 2016, Volume 25, pp. 153-164

https://doi.org/10.4467/20838476SI.16.012.6193

Authors

Mirosław Kordos
University of Bielsko-Biala Department of Computer Science, The University of Bielsko-Biala
, Poland
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Titles

Data Selection for Neural Networks

Abstract

Several approaches to joined feature and instance selection in neural network leaning are discussed and experimentally evaluated in respect to classification accuracy and dataset compression, considering also their computational complexity. These include various versions of feature and instance selection prior to the network learning, the selection embedded in the neural network and hybrid approaches, including solutions developed by us. The advantages and disadvantages of each approach are discussed and some possible improvements are proposed.

References

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Information

Information: Schedae Informaticae, 2016, Volume 25, pp. 153-164

Article type: Original scientific article

Authors

University of Bielsko-Biala Department of Computer Science, The University of Bielsko-Biala
Poland

Published at: 24.03.2017

Article status: Open

Licence: None

Percentage share of authors:

Mirosław Kordos (Author) - 100%

Article corrections:

-

Publication languages:

English

View count: 2546

Number of downloads: 5752

<p>Data Selection for Neural Networks</p>

12. Data Selection for Neural Networks

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