A Survey on the Explainability of Supervised Machine Learning
A Survey on the Explainability of Supervised Machine Learning
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Author / Creator
Publisher
San Francisco: AI Access Foundation
Journal title
Language
English
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Publication information
Publisher
San Francisco: AI Access Foundation
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Scope and Contents
Contents
Predictions obtained by, e.g., artificial neural networks have a high accuracy but humans often perceive the models as black boxes. Insights about the decision making are mostly opaque for humans. Particularly understanding the decision making in highly sensitive areas such as healthcare or finance, is of paramount importance. The decision-making b...
Alternative Titles
Full title
A Survey on the Explainability of Supervised Machine Learning
Authors, Artists and Contributors
Author / Creator
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Record Identifier
TN_cdi_proquest_journals_2553249126
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2553249126
Other Identifiers
ISSN
1076-9757
E-ISSN
1076-9757,1943-5037
DOI
10.1613/jair.1.12228
