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TEACHING COLLECTION

Naive Bayes and input variants

Distinguish Gaussian measurements from Bernoulli flags; match the likelihood to the input and inspect independence assumptions.

Helpful prior knowledge: Labels and probabilities · Encode categories without inventing order. These links are guidance, not locks.

Follow teaches the idea; Change asks you to make a choice; Transfer changes the context. Apply, reviews and checkpoints appear where the existing lessons provide them. Go Further lessons are optional.

Lessons in this model deck

Start with the first core lesson →

C15Core · teaching
Gaussian Naive Bayes: Class prior, Feature density, PosteriorClass AClass BClass priorFeature densityPosterior

Gaussian Naive Bayes

Combine class priors with continuous feature evidence.

25–40 min · 4 practices
C16Core · teaching
Match Naive Bayes to feature types: Input kind, Observed values, LikelihoodInput kindObservedvaluesLikelihoodbinary0 / 1Bernoullimeasuredreal valueGaussian

Match Naive Bayes to feature types

Use each production Naive Bayes preparation path.

18–25 min · 4 practices

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