02 Association Rules Example Using Support & Confidence | Data Mining (Sinhala)
In this video, I explain Association Rule Mining using a clear and practical example of a frequent itemset {A, B, E}, focusing on Support and Confidence calculations in Data Mining.
You will learn how to:
-Generate all possible association rules from a frequent itemset
-Apply minimum support (minsup) and minimum confidence (minconf) thresholds
-Identify which association rules satisfy minsup = 2 and minconf = 50%
-Understand how Support and Confidence are used to evaluate association rules
This example-based explanation helps you clearly understand how association rules such as
A → B,E , A,B → E , B → A,E , and others are evaluated in real Data Mining scenarios.
This video is especially useful for:
-University students
-IT / Computer Science students
-Data Mining and DBMS learners
-Exam and interview preparation
📌 Topic: Data Mining, Association Rule Mining, Support & Confidence
📌 Language: Sinhala (with English technical terms)
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