An Adaptive Neighborhood Retrieval Visualizer.

作者: Dominik Olszewski

DOI:

关键词: Information retrievalComputer science

摘要:

参考文章(15)
Dominik Olszewski, k -Means clustering of asymmetric data hybrid artificial intelligence systems. pp. 243- 254 ,(2012) , 10.1007/978-3-642-28942-2_22
Dominik Olszewski, Asymmetric k-Means Algorithm Adaptive and Natural Computing Algorithms. pp. 1- 10 ,(2011) , 10.1007/978-3-642-20267-4_1
Dominik Olszewski, An experimental study on asymmetric self-organizing map intelligent data engineering and automated learning. pp. 42- 49 ,(2011) , 10.1007/978-3-642-23878-9_6
Dominik Olszewski, Janusz Kacprzyk, Sławomir Zadrożny, Time Series Visualization Using Asymmetric Self-Organizing Map Adaptive and Natural Computing Algorithms. pp. 40- 49 ,(2013) , 10.1007/978-3-642-37213-1_5
S. Kullback, R. A. Leibler, On Information and Sufficiency Annals of Mathematical Statistics. ,vol. 22, pp. 79- 86 ,(1951) , 10.1214/AOMS/1177729694
T. Kohonen, The self-organizing map Proceedings of the IEEE. ,vol. 78, pp. 1464- 1480 ,(1990) , 10.1109/5.58325
Dominik Olszewski, Branko Šter, Asymmetric clustering using the alpha-beta divergence Pattern Recognition. ,vol. 47, pp. 2031- 2041 ,(2014) , 10.1016/J.PATCOG.2013.11.019
Dennis Ippoliti, Xiaobo Zhou, A-GHSOM: An adaptive growing hierarchical self organizing map for network anomaly detection Journal of Parallel and Distributed Computing. ,vol. 72, pp. 1576- 1590 ,(2012) , 10.1016/J.JPDC.2012.09.004
A. Rauber, D. Merkl, M. Dittenbach, The growing hierarchical self-organizing map: exploratory analysis of high-dimensional data IEEE Transactions on Neural Networks. ,vol. 13, pp. 1331- 1341 ,(2002) , 10.1109/TNN.2002.804221
Samuel Kaski, Kristian Nybo, Jarkko Venna, Jaakko Peltonen, Helena Aidos, Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization Journal of Machine Learning Research. ,vol. 11, pp. 451- 490 ,(2010)