Naive Bayes classifiers makes the naive assumption that the features are independent. They make use of Bayes theorem.
Naive Bayes classifiers make use of Bayes theorem:
$$\overbrace{P(c | X)}^{\text{A posteriori}} = \frac{\overbrace{P(X | c)}^{\text{Likelihood}} \cdot \overbrace{P(c)}^{\text{A priori} } }{\underbrace{P(X)}_{\text{evidence}}}$$
|
created |
7 years, 4 months ago by Martin Thoma |
|
viewed |
13 times |
|
active |
7 years, 4 months ago |
|
editors |
1 |
