Decision tree is one of the learning algorithm for classification or regression problems

Basically its a set of if then... else... rules for identifying a solution.

• Lecture start by giving various attributes or examples for going to a restaurant

• Then it deeply explains on the concept using the golf playing on saturday decision

• Best algorithm is ID3 for decision tree

• Other concepts like Entropy, Information gain are used to identify the best root node based on which the decision tree is build

• Cross validation can be done using testing the algorithm against the training data set using various combination of the models.

• When few cases does not have any proper data either the average of other similar data or same data as others are considered in order to identify the node