288 search results - page 16 / 58 » Bayesian Learning of Sparse Classifiers |
FLAIRS
2004
13 years 9 months ago
2004
We propose a new approach for learning Bayesian classifiers from data. Although it relies on traditional Bayesian network (BN) learning algorithms, the effectiveness of our approa...
PERCOM
2007
ACM
14 years 7 months ago
2007
ACM
Abstract. A major challenge in pervasive computing is to learn activity patterns, such as bathing and cleaning from sensor data. Typical sensor deployments generate sparse datasets...
KDD
1995
ACM
13 years 11 months ago
1995
ACM
The Bayesianclassifier is a simple approachto classification that producesresults that are easy for people to interpret. In many cases, the Bayesianclassifieris at leastasaccurate...
ICTAI
2008
IEEE
14 years 2 months ago
2008
IEEE
It is difficult to learn good classifiers when training data is missing attribute values. Conventional techniques for dealing with such omissions, such as mean imputation, general...
ML
2006
ACM
13 years 7 months ago
2006
ACM
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...