훈련용 검증용 테스트 데이터 세트 (Korean Wikipedia)

Analysis of information sources in references of the Wikipedia article "훈련용 검증용 테스트 데이터 세트" in Korean language version.

refsWebsite

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6doi.org

2^nd place

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6archive.org

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18^th place

5worldcat.org

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4machinelearningmastery.com

low place

2web.archive.org

1^st place

2usc.edu

1,077^th place

1,341^st place

2nih.gov

4^th place

1stanford.edu

179^th place

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1stackoverflow.com

4,643^rd place

1,744^th place

1coursera.org

low place

8,246^th place

1books.google.com

3^rd place

9^th place

1researchgate.net

120^th place

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archive.org (Global: 6^th place; Korean: 18^th place)

Bishop, Christopher M. (2006). 《Pattern Recognition and Machine Learning》. New York: Springer. vii쪽. ISBN 0-387-31073-8. Pattern recognition has its origins in engineering, whereas machine learning grew out of computer science. However, these activities can be viewed as two facets of the same field, and together they have undergone substantial development over the past ten years.
Ripley, Brian (1996). 《Pattern Recognition and Neural Networks》. Cambridge University Press. 354쪽. ISBN 978-0521717700.
Ripley, Brian (1996). 《Pattern Recognition and Neural Networks》. Cambridge University Press. 354쪽. ISBN 978-0521717700.
Prechelt, Lutz; Geneviève B. Orr (2012년 1월 1일). 〈Early Stopping — But When?〉. Grégoire Montavon; Klaus-Robert Müller (편집). 《Neural Networks: Tricks of the Trade》. Lecture Notes in Computer Science. Springer Berlin Heidelberg. 53–67쪽. 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.
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.

books.google.com (Global: 3^rd place; Korean: 9^th place)

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

coursera.org (Global: low place; Korean: 8,246^th place)

“Deep Learning” (영어). 《Coursera》. 2021년 5월 18일에 확인함.

doi.org (Global: 2^nd place; Korean: 3^rd place)

dx.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 (2012년 1월 1일). 〈Early Stopping — But When?〉. Grégoire Montavon; Klaus-Robert Müller (편집). 《Neural Networks: Tricks of the Trade》. Lecture Notes in Computer Science. Springer Berlin Heidelberg. 53–67쪽. 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.
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 (Global: low place; Korean: low place)

Brownlee, Jason (2017년 7월 13일). “What is the Difference Between Test and Validation Datasets?”. 2017년 10월 12일에 확인함.
Brownlee, Jason (2017년 7월 13일). “What is the Difference Between Test and Validation Datasets?”. 2017년 10월 12일에 확인함.
Brownlee, Jason (2017년 7월 13일). “What is the Difference Between Test and Validation Datasets?”. 2017년 10월 12일에 확인함.
Brownlee, Jason (2017년 7월 13일). “What is the Difference Between Test and Validation Datasets?”. 2017년 10월 12일에 확인함.

nih.gov (Global: 4^th place; Korean: 4^th place)

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.
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 (Global: 120^th place; Korean: 222^nd place)

Kohavi, Ron (2001년 3월 3일). “A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection” 14.

stackoverflow.com (Global: 4,643^rd place; Korean: 1,744^th place)

“Machine learning - Is there a rule-of-thumb for how to divide a dataset into training and validation sets?”. 《Stack Overflow》. 2021년 8월 12일에 확인함.

stanford.edu (Global: 179^th place; Korean: 146^th place)

ai.stanford.edu

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

usc.edu (Global: 1,077^th place; Korean: 1,341^st place)

www-bcf.usc.edu

James, Gareth (2013). 《An Introduction to Statistical Learning: with Applications in R》. Springer. 176쪽. ISBN 978-1461471370. 2019년 6월 23일에 원본 문서에서 보존된 문서. 2023년 12월 2일에 확인함.
James, Gareth (2013). 《An Introduction to Statistical Learning: with Applications in R》. Springer. 176쪽. ISBN 978-1461471370. 2019년 6월 23일에 원본 문서에서 보존된 문서. 2023년 12월 2일에 확인함.

web.archive.org (Global: 1^st place; Korean: 1^st place)

James, Gareth (2013). 《An Introduction to Statistical Learning: with Applications in R》. Springer. 176쪽. ISBN 978-1461471370. 2019년 6월 23일에 원본 문서에서 보존된 문서. 2023년 12월 2일에 확인함.
James, Gareth (2013). 《An Introduction to Statistical Learning: with Applications in R》. Springer. 176쪽. ISBN 978-1461471370. 2019년 6월 23일에 원본 문서에서 보존된 문서. 2023년 12월 2일에 확인함.

worldcat.org (Global: 5^th place; Korean: 11^th place)

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.
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.
Ripley, Brian D. (2009). 《Pattern recognition and neural networks》. Cambridge Univ. Press. Glossary쪽. ISBN 9780521717700. OCLC 601063414.

훈련용 검증용 테스트 데이터 세트 (Korean Wikipedia)

archive.org (Global: 6th place; Korean: 18th place)

books.google.com (Global: 3rd place; Korean: 9th place)

coursera.org (Global: low place; Korean: 8,246th place)

doi.org (Global: 2nd place; Korean: 3rd place)

dx.doi.org

machinelearningmastery.com (Global: low place; Korean: low place)

nih.gov (Global: 4th place; Korean: 4th place)