*2.1.2.2 How decision tree algorithm works?*

In the decision tree (DT), for predicting the class of the given dataset, the algorithm begins from the foundation node i.e., the decision node or root node of the tree. The algorithm compares the value of root characteristics with the record (real dataset) characteristics and based on the comparison the node is split on. For the subsequent node, the algorithm once more compares the attribute value with the alternative sub-node and circulates similarly. It keeps the manner until it reaches the leaf node of the tree. The whole technique can be better understood by the use of below algorithm:


Maintain this process until a degree is reached wherein you cannot further classify the nodes known as the final node known as the leaf node.
