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KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 7 months ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
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
KDD
2002
ACM
106views Data Mining» more  KDD 2002»
16 years 7 months ago
Selecting the right interestingness measure for association patterns
Many techniques for association rule mining and feature selection require a suitable metric to capture the dependencies among variables in a data set. For example, metrics such as...
Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava
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