Artificial Neural Network

 

  Decision Tree Algorithm o    Supervised machine learning algorithms. o    It is used for both a classification problem as well as for regression problem. o    It   predicts the value of a target variable(dependent variable) o    A decision tree represents a procedure for classifying   categorical data based on their attributes. o    The construction of decision tree does not require any   domain knowledge or parameter setting, and therefore   appropriate for exploratory knowledge discovery. o    Decision tree uses the tree representation to solve the problem in which the leaf node corresponds to a class label and attributes are represented on the internal node of the tree Decision Tree learning is one of the most widely used and practical methods for inductive inference over supervised   data. o    Their representation of acquired knowledge in tree form   is intuitive and easy to assimilate by humans. Decision Tree Classification  Example 1 Ø In above diagram leaf node