A New Tool for Automated Classification of Astronomical Images

摘要

Difference Boosting Neural Network (DBNN) is a variant of the Naive Bayesian Neural Network that assume parameter independence for computing the Bayesian Probability. Parameter independence is generally uncommon in practice and the performance of Naive Bayesian Networks degrades when the condition is not satisfied. DBNN, however, does not strictly require the parameters to be independent.