The SQL-MapReduce decision tree functions create a decision model that predicts an outcome based on a set of input variables. When constructing the tree, the splitting of branches stops when any of the stopping criteria is met.
The SQL-MapReduce decision tree functions support these predictive models:
| Model | Description |
|---|---|
| Regression problems (continuous response variable) | This model is used when the predicted outcome from the data is a real number. For example, the dollar amount of insurance claims for a year or the GPA expected for a college student. |
| Multiple-class classification (classification tree analysis) | This model is used to classify data by predicting to which provided classes the data belongs. For example, whether the input data is political news, economic news, or sports news. |
| Binary classification (binary response variable) | This model is used to make predictions when the outcome can be represented as a binary value (true/false, yes/no, 0/1). For example, whether the input insurance claim description data represents an accident. |