83 search results - page 1 / 17 » Lazy Learning of Bayesian Rules |
ICML
1999
IEEE
15 years 11 months ago
1999
IEEE
Lbr is a lazy semi-naive Bayesian classi er learning technique, designed to alleviate the attribute interdependence problem of naive Bayesian classi cation. To classify a test exa...
112
Voted
ML
2000
ACM
14 years 10 months ago
2000
ACM
The naive Bayesian classifier provides a simple and effective approach to classifier learning, but its attribute independence assumption is often violated in the real world. A numb...
87
Voted
AUSDM
2008
Springer
15 years 4 days ago
2008
Springer
LBR is a highly accurate classification algorithm, which lazily constructs a single Bayesian rule for each test instance at classification time. However, its computational complex...
JMLR
2010
14 years 5 months ago
2010
This paper introduces a Bayesian algorithm for constructing predictive models from data that are optimized to predict a target variable well for a particular instance. This algori...
ICML
2000
IEEE
15 years 11 months ago
2000
IEEE
As opposed to traditional supervised learning, multiple-instance learning concerns the problem of classifying a bag of instances, given bags that are labeled by a teacher as being...