Weighted Frequent Pattern Mining

Weighted frequent pattern mining involves the discovery of patterns in datasets where items are assigned different weights based on their significance. These patterns represent combinations of items that occur frequently and have a high cumulative weight relative to other patterns in the dataset. The main focus in weighted frequent pattern mining is to satisfy the downward closure property, which ensures that any subset of a frequent pattern is also frequent.

Applications: Market Basket Analysis, Healthcare Analytics, Network Traffic Analysis.

• Basic