Naive Bayes Classifier

Naive Bayes Classifier is a simple probabilistic classifiers based on applying Bayes' theorem with strong (naive) independence assumptions between the features.

Logic and algorithm guided by Mrs. Lili Ayu Wulandhari, S.Si., M.Sc., Ph.D.

What can I use this for?

• Sentiment analysis
• Document classify
• Forecasting
• And many things

Naive Bayes Classifier Formula

P(class|words) = (P(class)*P(words|class))/(P(words))

with assumtion that P(words) is the same for every class leeds to calculating so the new formula is

P(class|words) => P(class)*P(words|class)

• P(words|class) => P(word1|class) * P(word2|class) * P(wordn|class)
• P(class) => number of words in class divide by number of words in total

Version

1.0

• Initialize Project
• Language Added : PHP (v1.0)