Supervised learning (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Supervised learning" in English language version.

refsWebsite

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4,464^th place

4,468^th place

1,077^th place

761^st place

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207^th place

136^th place

2^nd place

2^nd place

1books.google.com

3^rd place

3^rd place

69^th place

59^th place

low place

low place

arxiv.org (Global: 69^th place; English: 59^th place)

A. Maity (2016). "Supervised Classification of RADARSAT-2 Polarimetric Data for Different Land Features". arXiv:1608.00501 [cs.CV].

books.google.com (Global: 3^rd place; English: 3^rd place)

Vapnik, V. N. The Nature of Statistical Learning Theory (2nd Ed.), Springer Verlag, 2000.

doi.org (Global: 2^nd place; English: 2^nd place)

M.R. Smith and T. Martinez (2011). "Improving Classification Accuracy by Identifying and Removing Instances that Should Be Misclassified". Proceedings of International Joint Conference on Neural Networks (IJCNN 2011). pp. 2690–2697. CiteSeerX 10.1.1.221.1371. doi:10.1109/IJCNN.2011.6033571.

jair.org (Global: low place; English: low place)

C.E. Brodely and M.A. Friedl (1999). Identifying and Eliminating Mislabeled Training Instances, Journal of Artificial Intelligence Research 11, 131–167. (http://jair.org/media/606/live-606-1803-jair.pdf)

psu.edu (Global: 207^th place; English: 136^th place)

citeseerx.ist.psu.edu

M.R. Smith and T. Martinez (2011). "Improving Classification Accuracy by Identifying and Removing Instances that Should Be Misclassified". Proceedings of International Joint Conference on Neural Networks (IJCNN 2011). pp. 2690–2697. CiteSeerX 10.1.1.221.1371. doi:10.1109/IJCNN.2011.6033571.

sipmm.edu.sg (Global: low place; English: low place)

publication.sipmm.edu.sg

"Key Technologies for Agile Procurement | SIPMM Publications". publication.sipmm.edu.sg. 2020-10-09. Retrieved 2022-06-16.

tau.ac.il (Global: 4,464^th place; English: 4,468^th place)

delta-apache-vm.cs.tau.ac.il

S. Geman, E. Bienenstock, and R. Doursat (1992). Neural networks and the bias/variance dilemma. Neural Computation 4, 1–58.

usc.edu (Global: 1,077^th place; English: 761^st place)

www-bcf.usc.edu

G. James (2003) Variance and Bias for General Loss Functions, Machine Learning 51, 115–135. (http://www-bcf.usc.edu/~gareth/research/bv.pdf)