Finding Frequent Itemsets: Difference between revisions

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== Parameters ==  
== Parameters ==  


No parameters found.
$n$: total number of transactions (size of database)


== Table of Algorithms ==  
== Table of Algorithms ==  

Revision as of 08:22, 10 April 2023

Description

We assume there is a number $s$, called the support threshold. If $I$ is a set of items, the support for $I$ is the number of baskets for which $I$ is a subset. We say $I$ is frequent if its support is $s$ or more

Parameters

$n$: total number of transactions (size of database)

Table of Algorithms

Name Year Time Space Approximation Factor Model Reference
A-Priori algorithm 1994 $O(n^{2})$ $O(n^{2})$ Exact Deterministic Time & Space
The Algorithm of Park; Chen; and Yu (PCY) 1995 $O(n^{2})$ $O(n^{2})$ Exact Deterministic Time
The Multistage Algorithm 1999 $O(n^{2})$ $O(n^{2})$ Exact Deterministic Time
The Multihash Algorithm 1999 $O(n^{2})$ $O(n^{2})$ Exact Deterministic Time

Time Complexity Graph

Finding Frequent Itemsets - Time.png

Space Complexity Graph

Finding Frequent Itemsets - Space.png

Time-Space Tradeoff

Finding Frequent Itemsets - Pareto Frontier.png