Association Rules Learning
May 13, 2024
2 minute read
Association Rules Learning, also known as market basket analysis, is a data mining technique that seeks to uncover relationships and correlations between different data items within a dataset. It is a widely used technique in business, finance, and other fields to extract valuable insights from large datasets and make informed decisions.
Why Learn Association Rules Learning?
There are several compelling reasons to learn Association Rules Learning:
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Find a path to becoming a Association Rules Learning. Learn more at:
OpenCourser.com/topic/zvs6qk/association
Reading list
We've selected five 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 Learning.
Provides a comprehensive overview of association rules learning, covering both theoretical and practical aspects. It is suitable as a textbook for a graduate-level course on data mining.
Covers association rules learning as part of a broader discussion of data mining concepts and techniques. It is suitable as a textbook for an undergraduate or graduate-level course on data mining.
Covers association rules learning as part of a broader discussion of machine learning algorithms. It is suitable as a textbook for an undergraduate or graduate-level course on machine learning.
Covers association rules learning as part of a broader discussion of data mining and knowledge discovery techniques. It is suitable as a textbook for a graduate-level course on data mining or knowledge discovery.
Briefly covers association rules learning as part of a broader discussion of data mining techniques for business intelligence. It is suitable as a textbook for a graduate-level course on data mining for business intelligence.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/zvs6qk/association