January 2019
Intermediate to advanced
294 pages
6h 43m
English
Content preview from Machine Learning Quick Reference
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The Bayes theorem
The Bayes theorem helps us in finding posterior probability, given a certain condition:
P(A|B)= P(B|A) * P(A)/P(B)
A and B can be deemed as the target and features, respectively.
Where, P(A|B): posterior probability, which implies the probability of event A, given that B has taken place:
- P(B|A): The likelihood that implies the probability of feature B, given the target A
- P(A): The prior probability of target A
- P(B): The prior probability of feature B
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