Decision tree learning uses a
decision tree as a
predictive model which maps observations about an item to conclusions about the item's target value. It is one of the predictive modelling approaches used in
statistics,
data mining and
machine learning. Tree models where the target variable can take a finite set of values are called
classification trees. In these tree structures,
leaves represent class labels and branches represent
conjunctions of features that lead to those class labels. Decision trees where the target variable can take continuous values (typically
real numbers) are called
regression trees.