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Incremental learning
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<h2 id="see-also">See also</h2> <ul><li><a href="/facts/Transduction_(machine_learning)/YBMCKGfo">Transduction (machine learning)</a></li></ul> <h2 id="external-links">External links</h2> <ul><li>charleslparker (March 12, 2013). <a href="https://blog.bigml.com/2013/03/12/machine-learning-from-streaming-data-two-problems-two-solutions-two-concerns-and-two-lessons/">"Brief Introduction to Streaming data and Incremental Algorithms"</a>. <i>BigML Blog</i>.</li> <li>Gepperth, Alexander; Hammer, Barbara (2016). <a href="https://www.esann.org/sites/default/files/proceedings/legacy/es2016-19.pdf"><i>Incremental learning algorithms and applications</i></a> (PDF). ESANN. pp. 357–368.</li> <li><a href="https://www.LibTopoART.eu">LibTopoART: A software library for incremental learning tasks</a></li> <li><a href="https://web.archive.org/web/20190803170741/https://creme-ml.github.io/">"Creme: Library for incremental learning"</a>. Archived from <a href="https://creme-ml.github.io">the original</a> on 2019-08-03.</li> <li>gaenari: <a href="https://github.com/greenfish77/gaenari">C++ incremental decision tree algorithm</a></li> <li>YouTube search results <a href="https://www.youtube.com/results?search_query=incremental+learning">Incremental Learning</a></li></ul> <h2 id="references">References</h2> <ol> <li id="fn:1"><p>Schlimmer, J. C., & Fisher, D. A case study of incremental concept induction. Fifth National Conference on Artificial Intelligence, 496-501. Philadelphia, 1986 <a href="https://www.researchgate.net/profile/Doug_Fisher2/publication/221603307_A_Case_Study_of_Incremental_Concept_Induction/links/555b1fc608ae980ca6122e64.pdf" target="_blank">https://www.researchgate.net/profile/Doug_Fisher2/publication/221603307_A_Case_Study_of_Incremental_Concept_Induction/links/555b1fc608ae980ca6122e64.pdf</a> <a href="#fnref:1" class="footnote-back-ref">↩</a></p></li> <li id="fn:2"><p>Utgoff, P. E., Incremental induction of decision trees. Machine Learning, 4(2): 161-186, 1989 <a href="http://people.cs.umass.edu/~utgoff/papers/mlj-id5r.pdf" target="_blank">http://people.cs.umass.edu/~utgoff/papers/mlj-id5r.pdf</a> <a href="#fnref:2" class="footnote-back-ref">↩</a></p></li> <li id="fn:3"><p>Ferrer-Troyano, Francisco, Jesus S. Aguilar-Ruiz, and Jose C. Riquelme. Incremental rule learning based on example nearness from numerical data streams. Proceedings of the 2005 ACM symposium on Applied computing. ACM, 2005 <a href="https://idus.us.es/xmlui/bitstream/handle/11441/39713/Incremental%20rule.pdf?sequence=4&isAllowed=y" target="_blank">https://idus.us.es/xmlui/bitstream/handle/11441/39713/Incremental%20rule.pdf?sequence=4&isAllowed=y</a> <a href="#fnref:3" class="footnote-back-ref">↩</a></p></li> <li id="fn:4"><p>Bruzzone, Lorenzo, and D. Fernàndez Prieto. An incremental-learning neural network for the classification of remote-sensing images. Pattern Recognition Letters: 1241-1248, 1999 <a href="https://rslab.disi.unitn.it/papers/R12-PRL-1999-11-13.pdf" target="_blank">https://rslab.disi.unitn.it/papers/R12-PRL-1999-11-13.pdf</a> <a href="#fnref:4" class="footnote-back-ref">↩</a></p></li> <li id="fn:5"><p>R. Polikar, L. Udpa, S. Udpa, V. Honavar. Learn++: An incremental learning algorithm for supervised neural networks. IEEE Transactions on Systems, Man, and Cybernetics. Rowan University USA, 2001. <a href="/wiki/Lalita_Udpa" target="_blank">/wiki/Lalita_Udpa</a> <a href="#fnref:5" class="footnote-back-ref">↩</a></p></li> <li id="fn:6"><p>G. Carpenter, S. Grossberg, N. Markuzon, J. Reynolds, D. Rosen. Fuzzy ARTMAP: a neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE transactions on neural networks, 1992 <a href="http://open.bu.edu/bitstream/handle/2144/2071/91.016.pdf?sequence=1" target="_blank">http://open.bu.edu/bitstream/handle/2144/2071/91.016.pdf?sequence=1</a> <a href="#fnref:6" class="footnote-back-ref">↩</a></p></li> <li id="fn:7"><p>Marko Tscherepanow, Marco Kortkamp, and Marc Kammer. A Hierarchical ART Network for the Stable Incremental Learning of Topological Structures and Associations from Noisy Data Archived 2017-08-10 at the Wayback Machine. Neural Networks, 24(8): 906-916, 2011 <a href="http://aiweb.techfak.uni-bielefeld.de/files/tscherepanow.marko2011ahierarchical-nn-r1.pdf" target="_blank">http://aiweb.techfak.uni-bielefeld.de/files/tscherepanow.marko2011ahierarchical-nn-r1.pdf</a> <a href="#fnref:7" class="footnote-back-ref">↩</a></p></li> <li id="fn:8"><p>Jean-Charles Lamirel, Zied Boulila, Maha Ghribi, and Pascal Cuxac. A New Incremental Growing Neural Gas Algorithm Based on Clusters Labeling Maximization: Application to Clustering of Heterogeneous Textual Data. IEA/AIE 2010: Trends in Applied Intelligent Systems, 139-148, 2010 <a href="https://www.researchgate.net/profile/Pascal_Cuxac/publication/47760684_A_new_incremental_neural_clustering_approach_for_performing_reliable_large_scope_scientometrics_analysis/links/58dbbb2c458515152b23f075/A-new-incremental-neural-clustering-approach-for-performing-reliable-large-scope-scientometrics-analysis.pdf" target="_blank">https://www.researchgate.net/profile/Pascal_Cuxac/publication/47760684_A_new_incremental_neural_clustering_approach_for_performing_reliable_large_scope_scientometrics_analysis/links/58dbbb2c458515152b23f075/A-new-incremental-neural-clustering-approach-for-performing-reliable-large-scope-scientometrics-analysis.pdf</a> <a href="#fnref:8" class="footnote-back-ref">↩</a></p></li> <li id="fn:9"><p>Diehl, Christopher P., and Gert Cauwenberghs. SVM incremental learning, adaptation and optimization Archived 2017-12-15 at the Wayback Machine. Neural Networks, 2003. Proceedings of the International Joint Conference on. Vol. 4. IEEE, 2003. <a href="http://www.isn.ucsd.edu/pubs/ijcnn03_inc.pdf" target="_blank">http://www.isn.ucsd.edu/pubs/ijcnn03_inc.pdf</a> <a href="#fnref:9" class="footnote-back-ref">↩</a></p></li> <li id="fn:10"><p>Carpenter, G.A., Grossberg, S., & Rosen, D.B., Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system, Neural Networks, 4(6): 759-771, 1991 <a href="http://dcommon.bu.edu/bitstream/handle/2144/2070/91.015.pdf?sequence=1&isAllowed=y" target="_blank">http://dcommon.bu.edu/bitstream/handle/2144/2070/91.015.pdf?sequence=1&isAllowed=y</a> <a href="#fnref:10" class="footnote-back-ref">↩</a></p></li> <li id="fn:11"><p>Marko Tscherepanow, Marco Kortkamp, and Marc Kammer. A Hierarchical ART Network for the Stable Incremental Learning of Topological Structures and Associations from Noisy Data Archived 2017-08-10 at the Wayback Machine. Neural Networks, 24(8): 906-916, 2011 <a href="http://aiweb.techfak.uni-bielefeld.de/files/tscherepanow.marko2011ahierarchical-nn-r1.pdf" target="_blank">http://aiweb.techfak.uni-bielefeld.de/files/tscherepanow.marko2011ahierarchical-nn-r1.pdf</a> <a href="#fnref:11" class="footnote-back-ref">↩</a></p></li> </ol>