Getting ready

You can download the dataset at https://archive.ics.uci.edu/ml/datasets/Car+Evaluation.

You need to treat each value in the dataset as a string. We consider six attributes in the dataset. Here are the attributes along with the possible values they can take:

• buying: These will be vhigh, high, med, and low.
• maint: These will be vhigh, high, med, and low.
• doors: These will be 2, 3, 4, 5, and more.
• persons: These will be 2, 4, and more.
• lug_boot: These will be small, med, and big.
• safety: These will be low, med, and high.

Given that each line contains strings, we need to assume that all the features are strings and design a classifier. In the previous chapter, we used random forests to build a regressor. In this recipe, we will use random forests as a classifier.