Handling classification errors by learning to reject classifications
نویسندگان
چکیده
منابع مشابه
Learning When to Reject an Importance Sample
When observations are incomplete or data are missing, approximate inference methods based on importance sampling are often used. Unfortunately, when the target and proposal distributions are dissimilar, the sampling procedure leads to biased estimates or requires a prohibitive number of samples. Our method approximates a multivariate target distribution by sampling from an existing, sequential ...
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ژورنال
عنوان ژورنال: Revista dos Trabalhos de Iniciação Científica da UNICAMP
سال: 2018
ISSN: 2596-1969
DOI: 10.20396/revpibic262018369