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Machine Learning Quick Reference

You're reading from  Machine Learning Quick Reference

Product type Book
Published in Jan 2019
Publisher Packt
ISBN-13 9781788830577
Pages 294 pages
Edition 1st Edition
Languages
Author (1):
Rahul Kumar Rahul Kumar
Profile icon Rahul Kumar
Toc

Table of Contents (18) Chapters close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Quantifying Learning Algorithms 2. Evaluating Kernel Learning 3. Performance in Ensemble Learning 4. Training Neural Networks 5. Time Series Analysis 6. Natural Language Processing 7. Temporal and Sequential Pattern Discovery 8. Probabilistic Graphical Models 9. Selected Topics in Deep Learning 10. Causal Inference 11. Advanced Methods 1. Other Books You May Enjoy Index

Association rules


Association rule mining is a technique that focuses upon observing frequently occurring patterns and associations from datasets found in databases such as relational and transactional databases. These rules do not say anything about the preferences of an individual; rather, they rely chiefly on the items within transactions to deduce a certain association. Every transaction is identified by a primary key (distinct ID) called, transaction ID. All these transactions are studied as a group and patterns are mined.

Association rules can be thought of as an if—then relationship. Just to elaborate on that, we have to come up with a rule: if an item A is being bought by the customer, then the chances of item B being picked by the customer too under the same transaction ID (along with item A) is found out. You needs to understand here that it's not a causality, rather, it is co-occurrence pattern that comes to the fore.

There are two elements of these rules:

  • Antecedent (if): This is...
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