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Association Rules

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May 1, 2024 3 minute read

Association Rule Mining is a technique used to discover interesting relationships, patterns, and correlations within data, specifically in large datasets. It's used in various industries, including retail, healthcare, finance, and manufacturing, to identify patterns and associations that can lead to insights and improved decision-making. Association rules are defined as implications in the form X => Y, where X and Y are itemsets, and the rule X => Y indicates that if X occurs in a transaction, then Y is also likely to occur.

How Association Rules Work

Association rule mining involves three main steps:

Path to Association Rules

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We've curated three courses to help you on your path to Association Rules. Use these to develop your skills, build background knowledge, and put what you learn to practice.

Sorted from most relevant to least relevant:

Association Rules Analysis

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Data Analysis with Python Project

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Data Preparation and Analysis

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Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Association Rules.

LATIN 2006: Theoretical Informatics

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Presents the seminal paper that introduced the concept of association rule mining. It provides a theoretical foundation for the field and discusses the Apriori algorithm.

LATIN 2006: Theoretical Informatics: 7th Latin...

Paperback

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LATIN 2006: Theoretical Informatics: 7th Latin...

Kindle Edition

Mining of Massive Datasets

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Covers association rule mining as part of its focus on big data mining techniques. It provides an overview of the topic and discusses applications in various domains.

Mining of Massive Datasets

Hardcover

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Introduction to Data Mining

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Includes a chapter on association rule mining, providing an introduction to the topic for readers seeking a general understanding of data mining concepts.

INTRODUCTION TO DATA MINING 2ND EDITION

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Introduction to Data Mining (2nd Edition) (What's...

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Introduction to Data Mining

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