Objectives
The objectives of this section are:
to explain the problem of frequent itemset generation
to introduce the main strategies for solving this problem
to explain the Apriori Principle
to explain the Apriori Algorithm and it's various parts
Outcomes
By the time you have completed this section you will be able to:
list the main strategies for solving the frequent itemset generation problem
describe the Apriori Principle
explain the major steps of the Apriori Algorithm
list the requirements for efficient Candidate Generation
distinguish between the methods for efficient Candidate Generation
Apriori Algorithm
The picture below represents the algorithm that is used
Apriori Generator Application
It is one thing to explain the concepts, it is quite another to see it in action. To get a hands on understanding of how this algorithm works click the link below to download an application that will allow you to build a decision tree for a particular dataset based on these measures. For instructions on how to use the Apriori Generator Application consult Help Section 5.
