Home > Model Nodes > Association Node > Classification Node > Edit Classification Build Node > Classification Node Properties > Advanced Settings Overview > Mining Functions > Classification > Building Classification Models
A classification model is built from historical data for which the classifications are known. To build (train) a classification model, a classification algorithm finds relationships between the values of the predictors and the values of the target. Different classification algorithms use different techniques for finding relationships. These relationships are summarized in a model; the model can then be applied to a different data set in which the class assignments are unknown.
Algorithm settings control model build. Settings depend on the algorithm.
Use a Build Node to build one or more classification models.
Classification models are tested by default. For information about testing and tuning classification models, see Testing Classification Models and Tuning Classification Models.