Naive Bayes Classifier in Tableau Without R or Python

Building machine learning algorithms or predictive models in Tableau requires R or Python integration or to push the model into your ETL process. This can be difficult for some organizations who don't have this capability or want to avoid stale models. My latest DuelingData post details how to build a Naive Bayes classification model entirely in Tableau that can scale as you feed it new data. 

Naive Bayes is a probabilistic classification model based on Bayes theorem. It can be used to predict the probability of an outcome based on multiple independent conditions. It is incredibly flexible, extensible, and simple. Naive Bayes classification models can be used to detect fraud, predict attrition, or diagnose medical conditions. Really it can potentially be used to determine the probability of any event occurring. 

The example detailed below is a proof of concept using Titanic passenger training data from a Kaggle challenge.

The following a a link to a detailed tutorial on how to build a Naive Bayes classifier model in Tableau and how to apply to new data: http://duelingdata.blogspot.com/2017/11/naive-bayes-classifier-in-tableau-no-rpy.html