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README.md
... | ... | @@ -1512,20 +1512,6 @@ To query nested data, use dot notation. |
1512 | 1512 | User.search "san", fields: ["address.city"], where: {"address.zip_code" => 12345} |
1513 | 1513 | ``` |
1514 | 1514 | |
1515 | -## Search Concepts | |
1516 | - | |
1517 | -### Precision and Recall | |
1518 | - | |
1519 | -[Precision and recall](https://en.wikipedia.org/wiki/Precision_and_recall) are two key concepts in search (also known as *information retrieval*). To help illustrate, let’s walk through an example. | |
1520 | - | |
1521 | -You have a store with 16 types of apples. A user searches for `apples` gets 10 results. 8 of the results are for apples, and 2 are for apple juice. | |
1522 | - | |
1523 | -**Precision** is the fraction of documents in the results that are relevant. There are 10 results and 8 are relevant, so precision is 80%. | |
1524 | - | |
1525 | -**Recall** is the fraction of relevant documents in the results out of all relevant documents. There are 16 apples and only 8 in the results, so recall is 50%. | |
1526 | - | |
1527 | -There’s typically a trade-off between the two. As you tweak your search to increase precision (not return irrelevant documents), there’s are greater chance a relevant document also isn’t returned, which decreases recall. The opposite also applies. As you try to increase recall (return a higher number of relevent documents), there’s a greater chance you also return an irrelevant document, decreasing precision. | |
1528 | - | |
1529 | 1515 | ## Reference |
1530 | 1516 | |
1531 | 1517 | Reindex one record | ... | ... |