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Unsupervised Learning · Recommenders
NMF
Recommender
Factor the buys matrix into k hidden tastes — the reconstruction fills the gaps and recommends.
▶ Factorise
↺ Reset
tastes k
V · who bought what
Ŵ·H · reconstructed
≈
iteration
0
error
—
state
press Factorise
bought (0–5)
recommendation
tip: low k = broad taste groups; high k = memorises every buy
nmf.py