Four failure archetypes emerge from 400 failed network-segmentation projects, with campus and VLAN-style projects overrepresented in the most failure-intensive groups.
Latent class cluster analysis
2 Pith papers cite this work, alongside 1,723 external citations. Polarity classification is still indexing.
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Pith papers citing it
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Benchmark on synthetic data finds learned-weights matching most accurate for intra-physician discordance estimation, with good rank preservation under separated groups.
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Why Network Segmentation Projects Fail
Four failure archetypes emerge from 400 failed network-segmentation projects, with campus and VLAN-style projects overrepresented in the most failure-intensive groups.
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How to measure intra-physician variability in clinical decision-making?
Benchmark on synthetic data finds learned-weights matching most accurate for intra-physician discordance estimation, with good rank preservation under separated groups.