66 search results - page 8 / 14 » Naive Bayes Classification of Uncertain Data |
TREC
2004
13 years 9 months ago
2004
We approached the problem of classifying papers for the TREC 2004 Genomics Track triage task as a four step process: feature generation, feature selection, classifier training, an...
SIGIR
2002
ACM
13 years 7 months ago
2002
ACM
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
IDEAL
2000
Springer
13 years 11 months ago
2000
Springer
Quantization of continuous variables is important in data analysis, especially for some model classes such as Bayesian networks and decision trees, which use discrete variables. Of...
KDD
2002
ACM
14 years 8 months ago
2002
ACM
Class membership probability estimates are important for many applications of data mining in which classification outputs are combined with other sources of information for decisi...
ICCV
2003
IEEE
14 years 9 months ago
2003
IEEE
This paper discusses building complex classifiers from a single labeled example and vast number of unlabeled observation sets, each derived from observation of a single process or...