Update Naive_Bayes_Classifiers.md

contrib/machine-learning/Naive_Bayes_Classifiers.md

@@ -75,7 +75,10 @@ In Gaussian Naive Bayes, continuous values associated with each feature are assu
 * Assumption: Each feature follows a Gaussian distribution.
 * Formula: The likelihood of the features given the class is computed using the Gaussian (normal) distribution formula:
 
-\( P(C_k | x) = \frac{1}{\sqrt{2\pi\sigma^2}} \exp\left(-\frac{(x - \mu)^2}{2\sigma^2}\right) \)
+$$
+P(C_k | x) = \frac{1}{\sqrt{2\pi\sigma^2}} \exp\left(-\frac{(x - \mu)^2}{2\sigma^2}\right)
+$$
+
 
 
 ![img_3.png](img_3.png)