Learning decision trees (English: Decision tree learning) is one way to approximate a function that is not continuous (discrete-value function) with the tree map can consist of a set of rules. If-then (if-then) so that humans can easily read and understand our decision tree.
.In machine learning (machine learning) is a mathematical model in decision tree that predicts the kind of object, based on the characteristics of the object. Non (inner node) of the tree displays the variable section, Beijing shows the possible values of the variable.
Tree establishment decided in business administration is a tree map helps in making a decision. By representing the value of the resource to be used in the risk investment and the results that have occurred. Most commonly used in risk management (risk management) decision trees as part of decision theory (decision theory), graph theory. The basic method of decision tree for data mining
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