[Verse 1]
Started with a dataset, features looking clean
Got some text to classify, know what I mean
Independence assumption, that's the naive part
Each feature stands alone, that's where we start
Prior probability, what we knew before
Evidence updates beliefs, opens up the door
Bayes theorem foundation, math that never lies
Posterior probability, that's our final prize
[Chorus]
Naive Bayes in the building, independence we assume
Prior times likelihood, evidence clears the room
Multiply probabilities, normalize the score
Classification magic, that's what we came for
Naive Bayes, naive but wise
Simple math that never lies
Independent features dance
Give predictions half a chance
[Verse 2]
Gaussian for continuous, bell curve in the mix
Multinomial for counting, word frequency tricks
Bernoulli for binary, zero or one choice
Each variant has purpose, each one has a voice
Training phase collecting, frequencies we count
Class conditional probabilities, every feature amounts
Laplace smoothing saves us when the zeros attack
Add one to numerator, keep the model on track
[Chorus]
Naive Bayes in the building, independence we assume
Prior times likelihood, evidence clears the room
Multiply probabilities, normalize the score
Classification magic, that's what we came for
Naive Bayes, naive but wise
Simple math that never lies
Independent features dance
Give predictions half a chance
[Bridge]
Spam detection classic, email filtering clean
Sentiment analysis, positive or mean
Medical diagnosis, symptoms tell the tale
Document classification, this method will not fail
Fast and scalable, handles big data streams
Baseline classifier, fulfilling ML dreams
[Verse 3]
Testing time approaching, new data at the gate
Calculate each class score, let probability fate
Argmax picks the winner, highest score takes all
Log space prevents underflow, keeps numbers from fall
Conditional independence, assumption might be wrong
But empirical results show this method staying strong
Interpretable and simple, transparent to the core
Naive Bayes classifier, couldn't ask for more
[Outro]
From prior to posterior, Bayes rule shows the way
Independence assumption, keeps complexity at bay
Naive but never foolish, elegant and clean
Naive Bayes classifier, best simple model you've seen