82 search results - page 1 / 17 » Learning Selective Averaged One-Dependence Estimators for Pr... |
FSKD
2007
Springer
13 years 11 months ago
2007
Springer
Naïve Bayes is a well-known effective and efficient classification algorithm, but its probability estimation performance is poor. Averaged One-Dependence Estimators, simply AODE,...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
Averaged One-Dependence Estimators (AODE) classifies by uniformly aggregating all qualified one-dependence estimators (ODEs). Its capacity to significantly improve naive Bayes...
ICDM
2009
IEEE
13 years 11 months ago
2009
IEEE
—It is well known that the key of Bayesian classifier learning is to balance the two important issues, that is, the exploration of attribute dependencies in high orders for ensu...
AUSAI
2005
Springer
13 years 10 months ago
2005
Springer
SuperParent-One-Dependence Estimators (SPODEs) loosen Naive-Bayes’ attribute independence assumption by allowing each attribute to depend on a common single attribute (superpare...
TWC
2010
12 years 11 months ago
2010
In this letter, we investigate the problem of CFO estimation in OFDM systems when the timing offset and channel length are not exactly known. Instead of explicitly estimating the t...