訓練・検証・テストデータセット (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "訓練・検証・テストデータセット" in Japanese language version.

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archive.org

Ripley, Brian (1996). Pattern Recognition and Neural Networks. Cambridge University Press. p. 354. ISBN 978-0521717700
Prechelt, Lutz; Geneviève B. Orr (2012-01-01). “Early Stopping — But When?”. In Grégoire Montavon; Klaus-Robert Müller. Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science. Springer Berlin Heidelberg. pp. 53–67. doi:10.1007/978-3-642-35289-8_5. ISBN 978-3-642-35289-8

books.google.com

Bishop, C.M. (1995), Neural Networks for Pattern Recognition, Oxford: Oxford University Press, p. 372

coursera.org

“Deep Learning” (英語). Coursera. 2021年5月18日閲覧。

doi.org

Ron Kohavi; Foster Provost (1998). “Glossary of terms”. Machine Learning 30: 271–274. doi:10.1023/A:1007411609915.
Prechelt, Lutz; Geneviève B. Orr (2012-01-01). “Early Stopping — But When?”. In Grégoire Montavon; Klaus-Robert Müller. Neural Networks: Tricks of the Trade. Lecture Notes in Computer Science. Springer Berlin Heidelberg. pp. 53–67. doi:10.1007/978-3-642-35289-8_5. ISBN 978-3-642-35289-8
Larose, D. T.; Larose, C. D. (2014). Discovering knowledge in data : an introduction to data mining. Hoboken: Wiley. doi:10.1002/9781118874059. ISBN 978-0-470-90874-7. OCLC 869460667
Xu, Yun; Goodacre, Royston (2018). “On Splitting Training and Validation Set: A Comparative Study of Cross-Validation, Bootstrap and Systematic Sampling for Estimating the Generalization Performance of Supervised Learning”. Journal of Analysis and Testing (Springer Science and Business Media LLC) 2 (3): 249–262. doi:10.1007/s41664-018-0068-2. ISSN 2096-241X. PMC 6373628. PMID 30842888.

machinelearningmastery.com

Brownlee, Jason (2017年7月13日). “What is the Difference Between Test and Validation Datasets?”. 2017年10月12日閲覧。

nih.gov

ncbi.nlm.nih.gov

Xu, Yun; Goodacre, Royston (2018). “On Splitting Training and Validation Set: A Comparative Study of Cross-Validation, Bootstrap and Systematic Sampling for Estimating the Generalization Performance of Supervised Learning”. Journal of Analysis and Testing (Springer Science and Business Media LLC) 2 (3): 249–262. doi:10.1007/s41664-018-0068-2. ISSN 2096-241X. PMC 6373628. PMID 30842888.

pubmed.ncbi.nlm.nih.gov

Xu, Yun; Goodacre, Royston (2018). “On Splitting Training and Validation Set: A Comparative Study of Cross-Validation, Bootstrap and Systematic Sampling for Estimating the Generalization Performance of Supervised Learning”. Journal of Analysis and Testing (Springer Science and Business Media LLC) 2 (3): 249–262. doi:10.1007/s41664-018-0068-2. ISSN 2096-241X. PMC 6373628. PMID 30842888.

researchgate.net

Kohavi, Ron (2001-03-03). A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection. 14.

stackoverflow.com

“Machine learning - Is there a rule-of-thumb for how to divide a dataset into training and validation sets?”. Stack Overflow. 2021年8月12日閲覧。

stanford.edu

ai.stanford.edu

Ron Kohavi; Foster Provost (1998). “Glossary of terms”. Machine Learning 30: 271–274. doi:10.1023/A:1007411609915.

usc.edu

www-bcf.usc.edu

James, Gareth (2013). An Introduction to Statistical Learning: with Applications in R. Springer. p. 176. ISBN 978-1461471370. http://www-bcf.usc.edu/~gareth/ISL/

wikipedia.org

en.wikipedia.org

en:Collaborative International Dictionary of English によれば、「証明すること、実験によって真実、真正性、または品質を証明すること」
Ron Kohavi; Foster Provost (1998). “Glossary of terms”. Machine Learning 30: 271–274. doi:10.1023/A:1007411609915.

worldcat.org

worldcat.org

Larose, D. T.; Larose, C. D. (2014). Discovering knowledge in data : an introduction to data mining. Hoboken: Wiley. doi:10.1002/9781118874059. ISBN 978-0-470-90874-7. OCLC 869460667
Ripley, Brian D. (2009). Pattern recognition and neural networks. Cambridge Univ. Press. pp. Glossary. ISBN 9780521717700. OCLC 601063414

search.worldcat.org

Xu, Yun; Goodacre, Royston (2018). “On Splitting Training and Validation Set: A Comparative Study of Cross-Validation, Bootstrap and Systematic Sampling for Estimating the Generalization Performance of Supervised Learning”. Journal of Analysis and Testing (Springer Science and Business Media LLC) 2 (3): 249–262. doi:10.1007/s41664-018-0068-2. ISSN 2096-241X. PMC 6373628. PMID 30842888.