Mg Charm Data Hiding Project Introduction:
The techniques of data mining have been used widely in various applications. Important applications of data mining is association rule mining. At present, almost all algorithms for association rule mining are based on Apriori algorithm. The MG-CHARM algorithm is a fast algorithm based on the CHARM algorithm which reduces the time for finding associations between the item sets. The prior method used level-wise mining method to find all mGs that correspond to each closed item set.
The numbers of frequent closed item sets (FCIs) are usually fewer than number of frequent item sets (FIs). However, it is necessary to find Minimal Generators (mGs) for mining association rules from them. The finding mGs approaches based on generating candidate loose timelines when the number of frequent closed item sets are large.
In this paper, we propose a Minimal Generators for Closed Hierarchical Association Rule Mining (abbreviated as MG-CHARM) based on CHARM which reduces the time for finding support between the item sets.
MG-CHARM reduces the complexity of Apriori based association rule mining techniques.
Data Hiding Project Intended Audience and Reading Suggestions
This project is intended to the people who are maintaining big organizations which have more transactions entries daily. They can analyze the group of customers and their intentions by using the final product. The readers should have prior software knowledge and data mining concepts before reading this document.
Download Mg Charm Data Hiding Project Source Code, Project Report, Documentation, PPT.