Citation Relationships

Legends: Link to a Model Reference cited by multiple papers

Huang D, Chow TWS (2005) Enhancing Density-Based Data Reduction Using Entropy Neural Comput 18:470-495

References and models cited by this paper

References and models that cite this paper

Astrahan MM (1970) Speech analysis by clustering, or the hyperphoneme method Stanford A I Project Memo
Bezdek JC, Kuncheva LI (2001) Nearest prototype classifier designs: An experimental study Int J Intell Sys 16:1445-1473
Blum AL, Langley P (1997) Selection of relevant feature and examples in machine learning Art Intell 97:245-271
Catlett J (1991) Megainduction: Machine learning on very large databases Unpublished doctoral dissertation
Chang CL (1974) Finding prototypes for nearest neighbor classifiers IEEE Trans Computers 23:1179-1184
Chow TWS, Wu S (2004) An online cellular probabilistic self-organizing map for static and dynamic data Sets IEEE Trans On Circuits And Systems 51:732-747
Cover TM, Thomas JA (1991) Elements of Information Theory
Dasarathy BV (1991) Nearest neighbor (NN) norms: NN pattern classification techniques
Duda RO, Hart PE, Stork DG (2000) Pattern Classification (2nd edition)
Friedman JH (1997) Data mining and statistics: What's the connection? Available online at
Gates GW (1972) The reduced nearest neighbor rule IEEE Trans on Inform Theory 18:431-433
Gersho A, Gray RM (1992) Vector quantization and signal compression
Gray RM (1984) Vector Quantization IEEE Assp Magazine 1:4-29
Han JW, Kamber M (2001) Data mining: Concepts and techniques
Hart PE (1968) The condensed nearest neighbor rule IEEE Trans On Information Theory 14:515-516
Haykin S (1999) Neural Networks: A Comprehensive Foundation (2nd Ed)
Khotanzad A, Lu JH (1990) Classification of invariant image representations using a neural network IEEE Transactions On Signal Process 38:1028-1038
Kohonen T (1995) Self-organizing Maps
Mitra P, Murthy CA, Pal SK (2002) Density-based multiscale data condensation IEEE Trans On PAMI 24:734-747
Parzen E (1962) On the estimation of a probability density function and mode Ann Math Stat 33:1064-1076
Plutowski M, White H (1993) Selecting concise training sets from clean data. IEEE Trans Neural Netw 4:305-18 [Journal] [PubMed]
Provost F, Kolluri V (1999) A survey of methods for scaling up inductive algorithms Data Mining And Knowledge Discovery 2:131-169
Quinlan R (1983) Learning efficient classification procedures and their application to chess end games Machine Learning-an Artificial Intelligence Approach, Michalski RS:Carbonell JG:Mitechell TM, ed. pp.463
Roy N, Mccallum A (2001) Toward optimal active learning through sampling estimation of error reduction Proc. 18th International Conference on Machine Learning (Available online at
Schapire RE (1990) The strength of weak learnability Machine Learning 5:197-227
Scott DW (1992) Multivariate density estimation: Theory, practice, and visualization
Wilson DR, Martinez TR (2000) Reduction techniques for instance-based learning algorithms Machine Learning 38:257-286
Yang ZP, Zwolinski M (2001) Mutual information theory for adaptive mixture models IEEE Trans On PAMI 23:396-403
(28 refs)