Decision tree
In decision theory (for example risk management), a decision tree is a graph of decisions and their possible consequences, (including resource costs and risks) used to create a plan to reach a goal. Decision trees are constructed in order to help with making decisions.
In machine learning, a decision tree is a predictive model; that is, a mapping of observations about an item to conclusions about the item's target value. Each inner node corresponds to variable; an arc to a child represents a possible value of that variable. A leaf represents the predicted value of target variable given the values of the variables represented by the path from the root. The machine learning technique for inducing a decision tree from data is called decision tree learning, or (colloquially) Decision Trees.
It is also a means for calculating conditional probabilities.
Referenced By
Decision table | List of graph theory topics | List of mathematical topics (D-F) | List of mathematical topics (F-Z)
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