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ICDM
2009
IEEE
107views Data Mining» more  ICDM 2009»
14 years 7 months ago
Naive Bayes Classification of Uncertain Data
Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from mea...
Jiangtao Ren, Sau Dan Lee, Xianlu Chen, Ben Kao, R...
KDD
2006
ACM
165views Data Mining» more  KDD 2006»
15 years 10 months ago
Training linear SVMs in linear time
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
Thorsten Joachims
CCGRID
2009
IEEE
15 years 4 months ago
Multi-scale Real-Time Grid Monitoring with Job Stream Mining
—The ever increasing scale and complexity of large computational systems ask for sophisticated management tools, paving the way toward Autonomic Computing. A first step toward A...
Xiangliang Zhang, Michèle Sebag, Céc...
PKDD
2009
Springer
118views Data Mining» more  PKDD 2009»
15 years 4 months ago
The Feature Importance Ranking Measure
Most accurate predictions are typically obtained by learning machines with complex feature spaces (as e.g. induced by kernels). Unfortunately, such decision rules are hardly access...
Alexander Zien, Nicole Krämer, Sören Son...
ICOST
2011
Springer
14 years 1 months ago
Using Association Rule Mining to Discover Temporal Relations of Daily Activities
The increasing aging population has inspired many machine learning researchers to find innovative solutions for assisted living. A problem often encountered in assisted living set...
Ehsan Nazerfard, Parisa Rashidi, Diane J. Cook