Case study

In this section, we will perform a case study with real-world machine learning datasets to illustrate some of the concepts from Bayesian networks.

We will use the UCI Adult dataset, also known as the Census Income dataset (http://archive.ics.uci.edu/ml/datasets/Census+Income). This dataset was extracted from the United States Census Bureau's 1994 census data. The donors of the data is Ronny Kohavi and Barry Becker, who were with Silicon Graphics at the time. The dataset consists of 48,842 instances with 14 attributes, with a mix of categorical and continuous types. The target class is binary.

Business problem

The problem consists of predicting the income of members of a population based on census data, specifically, whether their income is greater than $50,000.

Machine learning mapping

This is a problem of classification and this time around we will be training Bayesian graph networks to develop predictive models. We will be using linear, non-linear, and ensemble algorithms, as we...