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» Informative sampling for large unbalanced data sets
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SAC
2008
ACM
15 years 1 months ago
A clustering-based approach for discovering interesting places in trajectories
Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have...
Andrey Tietbohl Palma, Vania Bogorny, Bart Kuijper...
BMCBI
2007
148views more  BMCBI 2007»
15 years 1 months ago
Computation of significance scores of unweighted Gene Set Enrichment Analyses
Background: Gene Set Enrichment Analysis (GSEA) is a computational method for the statistical evaluation of sorted lists of genes or proteins. Originally GSEA was developed for in...
Andreas Keller, Christina Backes, Hans-Peter Lenho...
NIPS
1997
15 years 2 months ago
Active Data Clustering
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
Thomas Hofmann, Joachim M. Buhmann
CORR
2007
Springer
90views Education» more  CORR 2007»
15 years 1 months ago
Mutual information for the selection of relevant variables in spectrometric nonlinear modelling
Data from spectrophotometers form vectors of a large number of exploitable variables. Building quantitative models using these variables most often requires using a smaller set of...
Fabrice Rossi, Amaury Lendasse, Damien Franç...
CSL
2006
Springer
15 years 1 months ago
A study in machine learning from imbalanced data for sentence boundary detection in speech
Enriching speech recognition output with sentence boundaries improves its human readability and enables further processing by downstream language processing modules. We have const...
Yang Liu, Nitesh V. Chawla, Mary P. Harper, Elizab...