You are a machine learning specialist working for the social media software development division of your company. The social media features of your web applications allow users to post text messages and pictures about their experiences with your company’s products. You need to be able to block posts that contain inappropriate words quickly. You have defined a vocabulary of words deemed inappropriate for your site.
Which algorithm is best suited to your task?

Answer options:

A.Multinomial Naive Bayes
B.Bernoulli Naive Bayes
C.Gaussian Naive Bayes
D.Polychoric Naive Bayes

Answer: B
Option A is incorrect. The Multinomial Naive Bayes algorithm is best suited for document classification tasks where you wish to know the frequency of a given word from your vocabulary in your observed text. You need to know whether a word from your vocabulary appears in the given post text or not.
Option B is correct. The Bernoulli Naive Bayes algorithm is used in document classification tasks where you wish to know whether a word from your vocabulary appears in your observed text or not. This is exactly what you are trying to accomplish. You need to know whether a word from your vocabulary of inappropriate words appears in the given post text or not.
Option C is incorrect. The Gaussian Naive Bayes algorithm works continuous values in your observations, not discrete values. Your classification problem uses discrete data, the occurrence of a word or not.
Option D is incorrect. There is no Polychoric Naive Bayes algorithm.
Reference:
Please see the DatumBox page titled Machine Learning Blog & Software Development News (http://blog.datumbox.com/machine-learning-tutorial-the-naive-bayes-text-classifier/), the SebastianRaschka page titled Naive Bayes and Text Classification – Introduction and Theory (http://sebastianraschka.com/Articles/2014_naive_bayes_1.html#3_3_multivariate), the Medium page titled Naive Bayes Classifier (https://towardsdatascience.com/naive-bayes-classifier-81d512f50a7c), the Packt page titled Machine Learning Algorithms: Implementing Naive Bayes with Spark MLlib (https://hub.packtpub.com/machine-learning-algorithms-naive-bayes-with-spark-mllib/), the Wikipedia article page titled Naive Bayes classifier (https://en.wikipedia.org/wiki/Naive_Bayes_classifier)