148 search results - page 4 / 30 » Context-Based Distance Learning for Categorical Data Cluster... |
ICPR
2006
IEEE
14 years 8 months ago
2006
IEEE
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
BIRTHDAY
2010
Springer
13 years 10 months ago
2010
Springer
The present paper analyzes the usefulness of the normalized compression distance for the problem to cluster the hemagglutinin (HA) sequences of influenza virus data for the HA gene...
KDD
2002
ACM
14 years 7 months ago
2002
ACM
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
KDD
2007
ACM
14 years 7 months ago
2007
ACM
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...