Naive bayes theorem is applied assuming that each word is strongly independent and doesn't depend on occurrences of other words. • We find the posterior probability of each word given to test, based on the previously known probabilities and prior. • Prior is the chance whether an arbitrary mail is spam or non-spam, based on how frequently we receive them.
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Naive bayes theorem is applied assuming that each word is strongly independent and doesn't depend on occurrences of other words. • We find the posterior probability of each word given to test, based on the previously known probabilities and prior. • Prior is the chance whether an arbitrary mail is spam or non-spam, based on how frequently we rec…
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Alby0n/Spam-Email-Classifer-MATLAB
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Naive bayes theorem is applied assuming that each word is strongly independent and doesn't depend on occurrences of other words. • We find the posterior probability of each word given to test, based on the previously known probabilities and prior. • Prior is the chance whether an arbitrary mail is spam or non-spam, based on how frequently we rec…
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