To work properly, these functions require you to identify the columns that contain categorical input variables:
- CoxPH
- GLM
- GLM2
- GLML1L2
- Naive Bayes Classifier
- NaiveBayesPredict
- DecisionForest
- Forest_Predict
- XGBoost
If a column contains nonnumeric values, or numeric values that have no numeric relationship, identify the column as categorical.
For example, in the following table, the numeric values in the columns Area and Population have a numeric relationship—a higher number indicates a higher value. Therefore, Area and Population are numeric inputs. The numeric values in the column Region have no numeric relationship; they are labels. You must identify Region as a categorical column.
| State | Area (Thousand Sq. Mi.) | Population (Millions) | Region |
|---|---|---|---|
| New York | 54.60 | 19.7 | 1 |
| Pennsylvania | 46.00 | 12.8 | 1 |
| Georgia | 59.40 | 10.3 | 2 |
| Alabama | 52.40 | 4.9 | 2 |
| Iowa | 56.30 | 3.1 | 3 |
| Illinois | 57.90 | 12.8 | 3 |
You must identify a column of Boolean values as categorical, whether its values are nonnumeric (such as 'T' and 'F') or numeric (1 and 0).