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» Approximation in quantale-enriched categories
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96
Voted
KDD
2004
ACM
109views Data Mining» more  KDD 2004»
16 years 27 days ago
Identifying early buyers from purchase data
Market research has shown that consumers exhibit a variety of different purchasing behaviors; specifically, some tend to purchase products earlier than other consumers. Identifyin...
Paat Rusmevichientong, Shenghuo Zhu, David Selinge...
98
Voted
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 27 days 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
139
Voted
KDD
2003
ACM
191views Data Mining» more  KDD 2003»
16 years 27 days ago
Assessment and pruning of hierarchical model based clustering
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
Jeremy Tantrum, Alejandro Murua, Werner Stuetzle
94
Voted
KDD
2003
ACM
175views Data Mining» more  KDD 2003»
16 years 27 days ago
Time and sample efficient discovery of Markov blankets and direct causal relations
Data Mining with Bayesian Network learning has two important characteristics: under broad conditions learned edges between variables correspond to causal influences, and second, f...
Ioannis Tsamardinos, Constantin F. Aliferis, Alexa...
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 27 days ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny