Using scikit-learn, write a Random Forest classifier in Python. Submit the classifier in the form of an executable Python script alongside basic instructions for testing.

Your Random Forest classifier should allow you to do the following:

Calculate the posterior probability by converting the dataset into a frequency table.

Create a "Likelihood" table by finding relevant probabilities.

Calculate the posterior probability for each class.

Correct Zero Probability errors using Laplacian correction.