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» Data Mining: Machine Learning, Statistics, and Databases
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 1 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
AUSDM
2007
Springer
100views Data Mining» more  AUSDM 2007»
15 years 7 months ago
Determining Termhood for Learning Domain Ontologies using Domain Prevalence and Tendency
In the course of reviewing existing automatic term recognition techniques for applications in ontology learning, we came across four issues which can be improved upon. We proposed...
Wilson Wong, Wei Liu, Mohammed Bennamoun
KDD
1998
ACM
147views Data Mining» more  KDD 1998»
15 years 5 months ago
ADtrees for Fast Counting and for Fast Learning of Association Rules
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
Brigham S. Anderson, Andrew W. Moore
IDA
2000
Springer
15 years 1 months ago
From machine learning to knowledge discovery: Survey of preprocessing and postprocessing
Knowledge Discovery in Databases (KDD) has become a very attractive discipline both for research and industry within last few years. Its goal is to extract pieces of knowledge or `...
Ivan Bruha
ICDM
2010
IEEE
187views Data Mining» more  ICDM 2010»
14 years 11 months ago
Financial Forecasting with Gompertz Multiple Kernel Learning
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
Han Qin, Dejing Dou, Yue Fang