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» Generating Synthetic Data to Match Data Mining Patterns
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121
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SDM
2009
SIAM
175views Data Mining» more  SDM 2009»
16 years 1 months ago
Low-Entropy Set Selection.
Most pattern discovery algorithms easily generate very large numbers of patterns, making the results impossible to understand and hard to use. Recently, the problem of instead sel...
Hannes Heikinheimo, Jilles Vreeken, Arno Siebes, H...
152
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Towards robust word discovery by self-similarity matrix comparison
Word discovery is the task of discovering and collecting occurrences of repeating words in the absence of prior acoustic and linguistic knowledge, or training material. The capabi...
Armando Muscariello, Guillaume Gravier, Fré...
158
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GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
15 years 10 months ago
Exploring medical data using visual spaces with genetic programming and implicit functional mappings
Two medical data sets (Breast cancer and Colon cancer) are investigated within a visual data mining paradigm through the unsupervised construction of virtual reality spaces using ...
Julio J. Valdés, Robert Orchard, Alan J. Ba...
BMCBI
2007
115views more  BMCBI 2007»
15 years 4 months ago
A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector
Background: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) ...
Stephen Winters-Hilt, Carl Baribault
140
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PKDD
2004
Springer
131views Data Mining» more  PKDD 2004»
15 years 9 months ago
Asynchronous and Anticipatory Filter-Stream Based Parallel Algorithm for Frequent Itemset Mining
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...