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KDD
2006
ACM
115views Data Mining» more  KDD 2006»
16 years 7 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
KDD
2005
ACM
127views Data Mining» more  KDD 2005»
16 years 7 months ago
Detection of emerging space-time clusters
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
KDD
2004
ACM
154views Data Mining» more  KDD 2004»
16 years 7 months ago
Diagnosing extrapolation: tree-based density estimation
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
Giles Hooker
KDD
2004
ACM
134views Data Mining» more  KDD 2004»
16 years 7 months ago
Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pair
Given a user-specified minimum correlation threshold and a market basket database with N items and T transactions, an all-strong-pairs correlation query finds all item pairs with...
Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Ku...
KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 7 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
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