Decision Tree :The complete process can be better understood using the below algorithm:
- Step-1:Begin the tree with the root node, says S, which contains the complete dataset.
- Step-2:Find the best attribute in the dataset using Attribute Selection Measure (ASM).
- Step-3:Divide the S into subsets that contains possible values for the best attributes.
- Step-4:Generate the decision tree node, which contains the best attribute.
- Step-5:Recursively make new decision trees using the subsets of the dataset created in step -3. Continue this process until a stage is reached where you cannot further classify the nodes and called the final node as a leaf node.
