Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A view of the EM algorithm that justifies incremental, sparse, and other variants
Learning in graphical models
Fast density estimation using CF-kernel for very large databases
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Scalability for clustering algorithms revisited
ACM SIGKDD Explorations Newsletter
A streaming ensemble algorithm (SEA) for large-scale classification
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Accelerating EM for Large Databases
Machine Learning
A General Method for Scaling Up Machine Learning Algorithms and its Application to Clustering
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Better streaming algorithms for clustering problems
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Support Vector Data Description
Machine Learning
On demand classification of data streams
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Fast and Exact Out-of-Core K-Means Clustering
ICDM '04 Proceedings of the Fourth IEEE International Conference on Data Mining
Estimating the Support of a High-Dimensional Distribution
Neural Computation
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Efficient median based clustering and classification techniques for protein sequences
Pattern Analysis & Applications
Extensions of vector quantization for incremental clustering
Pattern Recognition
Efficient instance-based learning on data streams
Intelligent Data Analysis
Enhancing prototype reduction schemes with recursion: a method applicable for "large" data sets
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fuzzy clustering with volume prototypes and adaptive cluster merging
IEEE Transactions on Fuzzy Systems
The condensed nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
The reduced nearest neighbor rule (Corresp.)
IEEE Transactions on Information Theory
Multivariate online kernel density estimation with Gaussian kernels
Pattern Recognition
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In these years, we often deal with an enormous amount of data in a large variety of pattern recognition tasks. Such data require a huge amount of memory space and computation time for processing. One of the approaches to cope with these problems is using prototypes. We propose volume prototypes as an extension of traditional point prototypes. A volume prototype is defined as a geometric configuration that represents some data points inside. A volume prototype is akin to a data point in the usage rather than a component of a mixture model. We show a one-pass algorithm to have such prototypes for data stream, along with an application for classification. An oblivion mechanism is also incorporated to adapt concept drift.