Discussion
Which technique prevents a zero count from destroying an estimate?
Answer: B
Laplace smoothing adds a pseudocount to every cell before normalising, which keeps every probability strictly positive at a small cost in accuracy where data are plentiful. It amounts to a Dirichlet prior over the table. Discarding features loses information, rescaling distorts the ratios and neighbour averaging assumes an ordering that categorical values do not have. The Bayesian reading is what tells you how large the pseudocount should be.
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