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» Metrics for Mining Multisets
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
14 years 8 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
SDM
2009
SIAM
180views Data Mining» more  SDM 2009»
14 years 5 months ago
Structure and Dynamics of Research Collaboration in Computer Science.
Complex systems exhibit emergent patterns of behavior at different levels of organization. Powerful network analysis methods, developed in physics and social sciences, have been s...
Andre Nash, Christian Bird, Earl T. Barr, Premkuma...
KDD
2009
ACM
167views Data Mining» more  KDD 2009»
14 years 2 months ago
Anomalous window discovery through scan statistics for linear intersecting paths (SSLIP)
Anomalous windows are the contiguous groupings of data points. In this paper, we propose an approach for discovering anomalous windows using Scan Statistics for Linear Intersectin...
Lei Shi, Vandana Pursnani Janeja
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
14 years 1 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 11 months ago
Ensemble pruning via individual contribution ordering
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...
Zhenyu Lu, Xindong Wu, Xingquan Zhu, Josh Bongard