L2P predicts heavy-tailed outcome values by training a pairwise preference classifier and placing each new instance among training instances via a voting scheme.
Forecasting for inventory planning: a 50-year review
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
L2P: Learning to Place for Estimating Heavy-Tailed Distributed Outcomes
L2P predicts heavy-tailed outcome values by training a pairwise preference classifier and placing each new instance among training instances via a voting scheme.