: The performance of association rule algorithms is also evaluated based on time-complexity and accuracy of frequent
item set Also, Frequent item set is highly dependent on the user input status such as minimum support. It is difficult to know the
meticulous minimum support because these it generate logically incorrect or irrelevant FIS and sometime loose of worthy FIS.
These issues can be resolved with the help of Proposed Vertical Approach In this paper, a detailed comparison has been made
for the frequent pattern mining with normal approach and vertical approach with proper example. It shows that how can we
achieve logically relevant FIS as well as Produces FIS for few categories that are lesser in demand but have higher worth using
vertical approach. The Proposed vertical Approach provides a multi-level view of the dataset by clustering w.r.t. to category of
the product
