117 search results - page 2 / 24 » Boosting for Model-Based Data Clustering |
112
Voted
ICASSP
2010
IEEE
14 years 10 months ago
2010
IEEE
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
115
Voted
HIS
2004
15 years 2 months ago
2004
Boosting is a general method for improving the accuracy of a learning algorithm. AdaBoost, short form for Adaptive Boosting method, consists of repeated use of a weak or a base le...
91
Voted
ICML
2010
IEEE
15 years 2 months ago
2010
IEEE
Variable selection for cluster analysis is a difficult problem. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data ...
135
Voted
EPIA
2005
Springer
15 years 6 months ago
2005
Springer
In this paper, we propose a framework named UMT (User-profile Modeling based on Transactional data) for modeling user group profiles based on the transactional data. UMT is a gener...
128
Voted
JMLR
2002
15 years 24 days ago
2002
We examine the learning-curve sampling method, an approach for applying machinelearning algorithms to large data sets. The approach is based on the observation that the computatio...