GeneNSPCla uses negative sequential patterns mined by GONPM+ to add absence signals to viral genome features, raising average classifier accuracy by 10% over prior negative mining and 25% over positive mining.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DB 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Mining Negative Sequential Patterns to Improve Viral Genomic Feature Representation and Classification
GeneNSPCla uses negative sequential patterns mined by GONPM+ to add absence signals to viral genome features, raising average classifier accuracy by 10% over prior negative mining and 25% over positive mining.