Supervised learning (English Wikipedia)

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

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1books.google.com

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arxiv.org

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

books.google.com

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

doi.org

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

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

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

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

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

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)