Phi coefficient (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Phi coefficient" in English language version.

refsWebsite

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17doi.org

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16nih.gov

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3semanticscholar.org

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2harvard.edu

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2researchgate.net

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1archive.org

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1zenodo.org

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1ed.gov

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1arxiv.org

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1cawcr.gov.au

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1kvl.dk

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1scikit-learn.org

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1sciencedirect.com

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1worldcat.org

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archive.org

Cramer, H. (1946). Mathematical Methods of Statistics. Princeton: Princeton University Press, p. 282 (second paragraph). ISBN 0-691-08004-6 https://archive.org/details/in.ernet.dli.2015.223699

arxiv.org

Powers, David M. W. (10 October 2020). "Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation". arXiv:2010.16061 [cs.LG].

cawcr.gov.au

Brooks, Harold; Brown, Barb; Ebert, Beth; Ferro, Chris; Jolliffe, Ian; Koh, Tieh-Yong; Roebber, Paul; Stephenson, David (2015-01-26). "WWRP/WGNE Joint Working Group on Forecast Verification Research". Collaboration for Australian Weather and Climate Research. World Meteorological Organisation. Retrieved 2019-07-17.

doi.org

Matthews, B. W. (1975). "Comparison of the predicted and observed secondary structure of T4 phage lysozyme". Biochimica et Biophysica Acta (BBA) - Protein Structure. 405 (2): 442–451. doi:10.1016/0005-2795(75)90109-9. PMID 1180967.
Yule, G. Udny (1912). "On the Methods of Measuring Association Between Two Attributes". Journal of the Royal Statistical Society. 75 (6): 579–652. doi:10.2307/2340126. JSTOR 2340126.
Davenport, E.; El-Sanhury, N. (1991). "Phi/Phimax: Review and Synthesis". Educational and Psychological Measurement. 51 (4): 821–8. doi:10.1177/0013164491051004.
Boughorbel, S.B (2017). "Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric". PLOS ONE. 12 (6): e0177678. Bibcode:2017PLoSO..1277678B. doi:10.1371/journal.pone.0177678. PMC 5456046. PMID 28574989.
Chicco, D.; Tötsch, N.; Jurman, G. (2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (1): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Perruchet, P.; Peereman, R. (2004). "The exploitation of distributional information in syllable processing". J. Neurolinguistics. 17 (2–3): 97–119. doi:10.1016/s0911-6044(03)00059-9. S2CID 17104364.
Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465.
Chicco D, Jurman G (February 2023). "The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification". BioData Min. 16 (1): 4. doi:10.1186/s13040-023-00322-4. PMC 9938573. PMID 36800973.
Fawcett, Tom (2006). "An Introduction to ROC Analysis" (PDF). Pattern Recognition Letters. 27 (8): 861–874. doi:10.1016/j.patrec.2005.10.010. S2CID 2027090.
Ting, Kai Ming (2011). Sammut, Claude; Webb, Geoffrey I. (eds.). Encyclopedia of machine learning. Springer. doi:10.1007/978-0-387-30164-8. ISBN 978-0-387-30164-8.
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.
Chicco D, Toetsch N, Jurman G (February 2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (13): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Tharwat A. (August 2018). "Classification assessment methods". Applied Computing and Informatics. 17: 168–192. doi:10.1016/j.aci.2018.08.003.
Gorodkin, Jan (2004). "Comparing two K-category assignments by a K-category correlation coefficient". Computational Biology and Chemistry. 28 (5): 367–374. doi:10.1016/j.compbiolchem.2004.09.006. PMID 15556477.
Stoica P and Babu P (2024), Pearson–Matthews correlation coefficients for binary and multinary classification, Elsevier Signal Processing, 222, 109511, doi = https://doi.org/10.1016/j.sigpro.2024.109511
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.
Zhu, Qiuming (2020-08-01). "On the performance of Matthews correlation coefficient (MCC) for imbalanced dataset". Pattern Recognition Letters. 136: 71–80. Bibcode:2020PaReL.136...71Z. doi:10.1016/j.patrec.2020.03.030. ISSN 0167-8655. S2CID 219762950.

ed.gov

eric.ed.gov

Aaron, B., Kromrey, J. D., & Ferron, J. M. (1998, November). Equating r-based and d-based effect-size indices: Problems with a commonly recommended formula. Paper presented at the annual meeting of the Florida Educational Research Association, Orlando, FL. (ERIC Document Reproduction Service No. ED433353)

elte.hu

people.inf.elte.hu

Fawcett, Tom (2006). "An Introduction to ROC Analysis" (PDF). Pattern Recognition Letters. 27 (8): 861–874. doi:10.1016/j.patrec.2005.10.010. S2CID 2027090.

harvard.edu

ui.adsabs.harvard.edu

Boughorbel, S.B (2017). "Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric". PLOS ONE. 12 (6): e0177678. Bibcode:2017PLoSO..1277678B. doi:10.1371/journal.pone.0177678. PMC 5456046. PMID 28574989.
Zhu, Qiuming (2020-08-01). "On the performance of Matthews correlation coefficient (MCC) for imbalanced dataset". Pattern Recognition Letters. 136: 71–80. Bibcode:2020PaReL.136...71Z. doi:10.1016/j.patrec.2020.03.030. ISSN 0167-8655. S2CID 219762950.

jstor.org

Yule, G. Udny (1912). "On the Methods of Measuring Association Between Two Attributes". Journal of the Royal Statistical Society. 75 (6): 579–652. doi:10.2307/2340126. JSTOR 2340126.

kvl.dk

rk.kvl.dk

Gorodkin, Jan. "The Rk Page". The Rk Page. Retrieved 28 December 2016.

nih.gov

pubmed.ncbi.nlm.nih.gov

Matthews, B. W. (1975). "Comparison of the predicted and observed secondary structure of T4 phage lysozyme". Biochimica et Biophysica Acta (BBA) - Protein Structure. 405 (2): 442–451. doi:10.1016/0005-2795(75)90109-9. PMID 1180967.
Boughorbel, S.B (2017). "Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric". PLOS ONE. 12 (6): e0177678. Bibcode:2017PLoSO..1277678B. doi:10.1371/journal.pone.0177678. PMC 5456046. PMID 28574989.
Chicco, D.; Tötsch, N.; Jurman, G. (2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (1): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465.
Chicco D, Jurman G (February 2023). "The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification". BioData Min. 16 (1): 4. doi:10.1186/s13040-023-00322-4. PMC 9938573. PMID 36800973.
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.
Chicco D, Toetsch N, Jurman G (February 2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (13): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Gorodkin, Jan (2004). "Comparing two K-category assignments by a K-category correlation coefficient". Computational Biology and Chemistry. 28 (5): 367–374. doi:10.1016/j.compbiolchem.2004.09.006. PMID 15556477.
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.

ncbi.nlm.nih.gov

Boughorbel, S.B (2017). "Optimal classifier for imbalanced data using Matthews Correlation Coefficient metric". PLOS ONE. 12 (6): e0177678. Bibcode:2017PLoSO..1277678B. doi:10.1371/journal.pone.0177678. PMC 5456046. PMID 28574989.
Chicco, D.; Tötsch, N.; Jurman, G. (2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (1): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Chicco D (December 2017). "Ten quick tips for machine learning in computational biology". BioData Mining. 10 (35): 35. doi:10.1186/s13040-017-0155-3. PMC 5721660. PMID 29234465.
Chicco D, Jurman G (February 2023). "The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification". BioData Min. 16 (1): 4. doi:10.1186/s13040-023-00322-4. PMC 9938573. PMID 36800973.
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.
Chicco D, Toetsch N, Jurman G (February 2021). "The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation". BioData Mining. 14 (13): 13. doi:10.1186/s13040-021-00244-z. PMC 7863449. PMID 33541410.
Chicco D, Jurman G (January 2020). "The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation". BMC Genomics. 21 (1): 6-1–6-13. doi:10.1186/s12864-019-6413-7. PMC 6941312. PMID 31898477.

researchgate.net

Provost, Foster; Tom Fawcett (2013-08-01). "Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking". O'Reilly Media, Inc.
Powers, David M. W. (2011). "Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness & Correlation". Journal of Machine Learning Technologies. 2 (1): 37–63.

sciencedirect.com

Zhu, Qiuming (2020-08-01). "On the performance of Matthews correlation coefficient (MCC) for imbalanced dataset". Pattern Recognition Letters. 136: 71–80. Bibcode:2020PaReL.136...71Z. doi:10.1016/j.patrec.2020.03.030. ISSN 0167-8655. S2CID 219762950.

scikit-learn.org

"Matthew Correlation Coefficient". scikit-learn.org.

semanticscholar.org

api.semanticscholar.org

Perruchet, P.; Peereman, R. (2004). "The exploitation of distributional information in syllable processing". J. Neurolinguistics. 17 (2–3): 97–119. doi:10.1016/s0911-6044(03)00059-9. S2CID 17104364.
Fawcett, Tom (2006). "An Introduction to ROC Analysis" (PDF). Pattern Recognition Letters. 27 (8): 861–874. doi:10.1016/j.patrec.2005.10.010. S2CID 2027090.
Zhu, Qiuming (2020-08-01). "On the performance of Matthews correlation coefficient (MCC) for imbalanced dataset". Pattern Recognition Letters. 136: 71–80. Bibcode:2020PaReL.136...71Z. doi:10.1016/j.patrec.2020.03.030. ISSN 0167-8655. S2CID 219762950.

worldcat.org

search.worldcat.org

Zhu, Qiuming (2020-08-01). "On the performance of Matthews correlation coefficient (MCC) for imbalanced dataset". Pattern Recognition Letters. 136: 71–80. Bibcode:2020PaReL.136...71Z. doi:10.1016/j.patrec.2020.03.030. ISSN 0167-8655. S2CID 219762950.

zenodo.org

Yule, G. Udny (1912). "On the Methods of Measuring Association Between Two Attributes". Journal of the Royal Statistical Society. 75 (6): 579–652. doi:10.2307/2340126. JSTOR 2340126.