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