A hybrid heuristic algorithm for evolving models in simultaneous scenarios of classification and clustering

Author:

Cerrada Mariela,Aguilar JoseORCID,Altamiranda Junior,Sánchez René-Vinicio

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Reference46 articles.

1. Aggarwal CC, Han J, Wang J, Yu PS (2006) A framework for on-demand classification of evolving data streams. IEEE Trans Knowl Data Eng 18(5):577–589

2. Amini A, Saboohi H, Herawan T, Wah TY (2016) Mudi-stream: a multi density clustering algorithm for evolving data stream. J Netw Comput Appl 59:370–385

3. Basu S (2004) A comparison of inference techniques for semi-supervised clustering with Hidden Markov random fields. In: Proceedings of the ICML-2004 workshop on statistical relational learning and its connections to other fields

4. Bishop C (2006) Pattern recognition and machine learning. Springer, Cambridge

5. Bordignon F, Gomide F (2014) Uninorm based evolving neural networks and approximation capabilities. Neurocomputing 127:13–20

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