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KDD
2008
ACM
14 years 10 months ago
2008
ACM
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
KDD
2008
ACM
14 years 10 months ago
2008
ACM
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...
KDD
2008
ACM
14 years 10 months ago
2008
ACM
This paper presents a new algorithm for sequence prediction over long categorical event streams. The input to the algorithm is a set of target event types whose occurrences we wis...
KDD
2008
ACM
14 years 10 months ago
2008
ACM
Frequent patterns provide solutions to datasets that do not have well-structured feature vectors. However, frequent pattern mining is non-trivial since the number of unique patter...
KDD
2009
ACM
14 years 10 months ago
2009
ACM
Corruption of data by class-label noise is an important practical concern impacting many classification problems. Studies of data cleaning techniques often assume a uniform label ...