Exact vs Normalised Matching: How Many True Matches Do You Find?
This lesson is part of the course
In this lesson
You compare twelve pairs that are known to be the same customer with three methods (EXACT, a simple =, and a reusable Norm LAMBDA) and measure each method's match rate.
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Lessons in this course
- Normalising Company Names: TRIM, LOWER, SUBSTITUTE and Legal Suffixes Locked
- Blocking Keys: First Letter + Postcode to Limit Comparisons Locked
- Exact vs Normalised Matching: How Many True Matches Do You Find? Locked
- Character Bigram Similarity: Jaccard and Dice with MID and SEQUENCE Locked
- Token Overlap for Company Names: Word Jaccard and the Overlap Coefficient Locked
- Combined Match Score: Weights and Two Thresholds (Match, Review, Non-Match) Locked
- Precision and Recall of the Matcher against a Labelled Sample Locked
- De-duplication: Cluster IDs, the Golden Record and the Score Distribution Locked