Random projection large margin algorithm for binary classification problems

doi:10.1016/j.asoc.2025.114180

Random projection large margin algorithm for binary classification problems

2025-11-05

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Vítor Gabriel Reis Caitité *

DOI：10.1016/j.asoc.2025.114180

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• A large-margin classifier ( - Random Projection - Incremental Margin Algorithm) presented for SLFNs using random explicit feature mapping. • achieved average accuracy, significantly outperforming the equivalent Extreme Learning Machine ( ) configuration ( ). • overall accuracy performance is highly competitive with established large-margin methods: Support Vector Machine ( ) and Large Margin Nearest Neighbor ( ). • An -based pruning scheme reduced the network architecture by up to while preserving classification accuracy.

Random projection large margin algorithm for binary classification problems

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