Margin Elo (MELO) – new ML algorithm for pairwise comparison

What it does

melo generalizes the Bradley-Terry paired comparison model beyond binary outcomes to include margin-of-victory information. It does this by “redefining what it means to win” using a variable handicap to shift the threshold of paired comparison. The framework is general and has numerous applications in ranking, estimation, and time series prediction. import pkgutil import numpy as np from melo import Melo # the package comes pre-bundled with an example dataset pkgdata = pkgutil . get_data ( 'melo' , 'nfl.dat' ) . splitlines () dates , teams_home , scores_home , teams_away , scores_away = zip ( * [ l . split () for l in pkgdata [ 1 :]]) # define a binary comparison statistic spreads = [ int (…from moreland.dev

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