A Naive Bayes’ classifier naively assumes that each of the descriptive features in a domain ¡s conditionally independent of all of the other descriptive features, given the state of the target feature.

computer science

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Summary

P(dlt) x P(t)

P(tld) P(d) (2)

. A Naive Bayes’ classifier naively assumes that each of the descriptive features in a domain ¡s conditionally independent of all of the other descriptive features, given the state of the target feature.

. This assumption, although often wrong, enables the Naive Bayes’ model to maximally factorise the representation that it uses of the domain.

. Surprisingly, given the naivety and strength of the assumption it depends upon, a Naive Bayes’ model often performs reasonably well.

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