Many Categories Impurity
Learn how CART decision trees handle categorical features with more than two categories.
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Multivalue attributes
When building decision trees, the CART algorithm uses only two-way (i.e., binary) data splits. CART classification trees are constructed using the Gini gain calculation. This lesson expands this knowledge by teaching how the CART classification tree algorithm handles a widespread situation in business data—categorical features with more than two values.
Consider the following Adult Census Income data sample:
Adult Census Income Data Sample
Occupation | Income |
Adm-clerical | <=50K |
Exec-managerial | <=50K |
Handlers-cleaners | <=50K |
Handlers-cleaners | <=50K |
Prof-specialty | <=50K |
Exec-managerial | <=50K |
Other-service | <=50K |
Exec-managerial | >50K |
Prof-specialty | >50K |
Exec-managerial | >50K |
In this data sample, the occupation feature has five distinct