• A decision tree is tree in which each branch node represents a choice between a number of alternatives and each leaf node represents a classification or decision.
  • Decision tree is a classifier in the form of a tree structure where a leaf node indicates the class of instances, a decision node specifies some test to be carried out on a single attribute value with one branch and sub-tree for each possible outcome of the test.
  • A decision tree can be used to classify an instance by starting at root of the tree and moving through it until leaf node. The leaf node provides the corresponding class of instance.


Decision Tree Algorithm

  1. Hunt’s Algorithm
  2. ID3, J48, 5 (Based on Entropy Calculation)
  3. SLIQ,SPRINT,CART (Based on Gini-Index)

Advantages of Decision Tree Classifier

  • Inexpensive to construct
  • Extremely fast at classifying unknown records
  • Easy to interpret for small-sized trees
  • Accuracy is comparable to other classification techniques for many simple data sets