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What is Naive Bayes ?
It works based on the conditional probability as given by the Bayes Theorem. If we toss two coin and look at all the different possible outcomes, we have the sample space as : {HH, HT, TH, TT}
Bayes' theorem is also known as Bayes' Rule or Bayes' law, which is used to determine the probability of a hypothesis with prior knowledge. It depends on the conditional probability
The formula for Bayes' theorem is given as:
Where,
P(A|B) is Posterior probability: Probability of hypothesis A on the observed event B.
P(B|A) is Likelihood probability: Probability of the evidence given that the probability of a
hypothesis is true.
During calculating the math on probability, we usually denote probability as P. Some of the probabilities in this event would be as follows:
The probability of getting two heads = 1/4
The probability of at least one tail = 3/4
The probability of the second coin being head given the first coin is tail = 1/2
The probability of getting two heads given the first coin is a head = 1/2
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