Frequent Itemset Mining In Data Mining

1376 Words3 Pages

ABSTRACT: Frequent Itemset mining is an important concept in Data Mining. With the development of complex applications, huge amount of data is received from the user and collectively stored. In order to make these applications profitable, the stakeholders need to understand important patterns from this data which occur frequently so that the system can be modified or updated as per the evaluated result. The business now-a-days being fast paced, it is important for the frequent itemset mining algorithms to be fast. This paper compares the performance of four such algorithms viz Apriori, ECLAT, FPgrowth and PrePost algorithm on the parameters of total time required and maximum memory usage.

I. INTRODUCTION

Data mining, or knowledge discovery, is the computer-driven process of searching through and analysing enormous data and then understanding the meaning of the data. Data mining helps predict future trends which allow businesses to make …show more content…

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