In this paper we test several approaches to analysing grapheme codebook features for offline writer identification in medieval English scribal manuscripts. Current methods for selecting a codebook typically produce codebooks that perform no better than random grapheme selection, so our aim in this analysis is to identify potential methods of improving codebook selection. Three feature extractio...

Consider feature selection is the main in intelligent algorithms and machine learning to select subset of data help acquire optimal solution. Feature used an extract relevance discarding irrelevance with increment fast it reduce dimensional dataset. In past, traditional methods, but these methods are slow accuracy. modern times, however, uses Genetic algorithm swarm optimization Ant colony, Bee...

Sorted L-One Penalized Estimation (SLOPE) has shown the nice theoretical property as well empirical behavior recently on false discovery rate (FDR) control of high-dimensional feature selection by adaptively imposing non-increasing sequence tuning parameters sorted L1 penalties. This paper goes beyond previous concern limited to FDR considering stepdown-based SLOPE in order probability k or mor...

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