Probabilistic Feature Selection and Classification Vector Machine
نویسندگان
چکیده
منابع مشابه
Probabilistic Feature Selection and Classification Vector Machine
Sparse Bayesian learning is one of the state-ofthe-art machine learning algorithms, which is able to make stable and reliable probabilistic predictions. However, some of these algorithms, e.g. probabilistic classification vector machine (PCVM) and relevant vector machine (RVM), are not capable of eliminating irrelevant and redundant features which could lead to performance degradation. To tackl...
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Background: In the current study, a hybrid feature selection approach involving filter and wrapper methods is applied to some bioscience databases with various records, attributes and classes; hence, this strategy enjoys the advantages of both methods such as fast execution, generality, and accuracy. The purpose is diagnosing of the disease status and estimating of the patient survival. Method...
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ژورنال
عنوان ژورنال: ACM Transactions on Knowledge Discovery from Data
سال: 2019
ISSN: 1556-4681,1556-472X
DOI: 10.1145/3309541