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DATA MINING · R + JMP
Book Interaction & Association Rule Mining
An end-to-end Book-BX analysis combining data cleaning, exploratory analysis and association-rule mining using Support, Confidence and Lift.
PROJECT OVERVIEW
What the project covers
An end-to-end Book-BX analysis combining data cleaning, exploratory analysis and association-rule mining using Support, Confidence and Lift.
The project is based on the Book-BX dataset and is presented for educational and portfolio purposes.
RJMPData CleaningEDAAssociation RulesSupport / Confidence / Lift
APPROACH
What I did
- Cleaned user age, missing values, publication-year issues and rating-related fields.
- Extracted geographic attributes and built descriptive views for books, authors, publishers and users.
- Used JMP for exploratory analysis and R for association-rule mining.
- Evaluated rules using Support, Confidence and Lift rather than frequency alone.
KEY FINDINGS
What came out of the analysis
- Age values outside a plausible range were treated as missing during cleaning, producing a more reliable user-age field.
- Descriptive analysis highlighted concentration among a subset of authors, publishers, books and countries.
- Association-rule mining identified strong co-occurrence patterns, including notable relationships among books in The Green Mile series.
- The project demonstrates R as part of a complete data-mining workflow rather than as an isolated listed skill.
FULL REPORT
Analysis report
38-page report. Report language: Persian.
Book Interaction & Association Rule Mining38 pages · PDF · Persian
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