Finding Frequent Patterns Based On Quantitative Binary Attributes Using FP-Growth Algorithm

摘要

Discovery of frequent patterns fro m a large database is considered as an important aspect of data mining. There is always an ever increasing d emand to find the frequent patterns. This paper introduces a method to handle the categorical attributes and numerical attributes in an efficient way. In the proposed methodology, ordinary database is converted in to quantitative database and hence it is converted in to binary values depending on the condition of the student database. From the binary patterns of all attributes presented in the student database, the frequent patterns are identified using FP growth,The conversion reveals all the frequent patterns in the student database