A Dynamic Adaptation of AD-trees for Efficient Machine Learning on Large Data Sets (2000)

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by Paul Komarek , Andrew Moore
Citations:15 - 5 self

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A Dynamic Adaptation of AD-trees for Efficient Machine Learning – On Large Data, Paul Komarek - 2000
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes – Giovanni Giurida, Wesley W. Chu, Dominique M. Hanssens - 2000
1 Cached Sufficient Statistics for Automated Mining and Discovery from Massive Data Sources – Andrew Moore, Jeff Schneider, Brigham Anderson Brighamcs. Cmu. Edu, Paul Komarek Komarekcs. Cmu. Edu, Remi Munos Munoscs. Clm. Edu, Kary Myers Karycs. Cmu. Edu, Dan Pelleg Dpellegcs. Cmu. Edu - 2000
75 The Anchors Hierarchy: Using the Triangle Inequality to Survive High Dimensional Data – Andrew W. Moore - 2000
4 Summary of biosurveillance-relevant technologies – Andrew Moore, Greg Cooper, Rich Tsui, Mike Wagner - 2003
1 Itemset support queries using frequent itemsets and their condensed representations – Taneli Mielikäinen, Panče Panov - 2006
Mining Customer Value: From . . . – Ke Wang, Qiang Yang, Senqiang Zhou, Jack Man Shun Yeung
2 Machine Learning as Massive Search – Richard B. Segal - 1997
21 Propositionalization-based relational subgroup discovery with RSD – Filip ˇzelezn´y Nada Lavrač - 2006
17 Knowledge Discovery from Sequential Data – Frank Höppner - 2003
2 A Scalable Bottom-Up Data Mining Algorithm for Relational Databases – Giovanni Giuffrida, Lee G. Cooper, Wesley W. Chu - 1998
3 Fast Factored Density Estimation and Compression with Bayesian Networks – Scott Davies, John Lafferty - 2002
Operations and Evaluation Measures for Learning Possibilistic Graphical Models – Christian Borgelt, Rudolf Kruse
3 Learning and Planning in Structured Worlds – Richard W. Dearden - 2000
Handbook of Perception and Cognition, Vol.14 Chapter 4: Machine Learning – Stuart Russell
9 FlexiMine - a flexible platform for KDD research and application construction – C. Domshlak, D. Gershkovich, E. Gudes, N. Liusternik, A. Meisels, T. Rosen, S. E. Shimony - 1998
13 Bayesian network classifiers for identifying the slope of the customer lifecycle of long-life customers – Bart Baesens , Geert Verstraeten , Dirk Van Den Poel , et al. - 2004
8 Machine Learning – Stuart Russell
2 Symbolic, Neural, and Bayesian Machine Learning Models for Predicting Carcinogenicity of Chemical Compounds – Dennis Bahler, Brian Stone, Carol Wellington, Douglas W. Bristol - 2000