Adding L2 norm technique #236
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Signed-off-by: Martin Gaievski <[email protected]>
Signed-off-by: Martin Gaievski <[email protected]>
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Codecov Report
@@ Coverage Diff @@
## feature/normalization #236 +/- ##
===========================================================
- Coverage 85.95% 82.43% -3.53%
- Complexity 310 323 +13
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Files 24 26 +2
Lines 904 979 +75
Branches 137 153 +16
===========================================================
+ Hits 777 807 +30
- Misses 67 108 +41
- Partials 60 64 +4
|
heemin32
reviewed
Jul 28, 2023
.../java/org/opensearch/neuralsearch/processor/normalization/L2ScoreNormalizationTechnique.java
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Signed-off-by: Martin Gaievski <[email protected]>
heemin32
approved these changes
Jul 28, 2023
navneet1v
approved these changes
Jul 31, 2023
HenryL27
reviewed
Jul 31, 2023
Comment on lines
+49
to
+65
| public float combine(final float[] scores) { | ||
| float combinedScore = 0.0f; | ||
| float weights = 0; | ||
| for (int indexOfSubQuery = 0; indexOfSubQuery < scores.length; indexOfSubQuery++) { | ||
| float score = scores[indexOfSubQuery]; | ||
| if (score >= 0.0) { | ||
| float weight = getWeightForSubQuery(indexOfSubQuery); | ||
| score = score * weight; | ||
| combinedScore += score; | ||
| weights += weight; | ||
| } | ||
| } | ||
| if (weights == 0.0f) { | ||
| return ZERO_SCORE; | ||
| } | ||
| return combinedScore / weights; | ||
| } |
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weighted harmonic mean = sum(wi) / sum(1/(wi*si))
https://en.wikipedia.org/wiki/Harmonic_mean
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Thanks @HenryL27 , that's what I'm working now and it will be a new PR for harmonic mean and weighted geometric combination. Probably checked in this class incidentally in a half-ready form.
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Description
Adding L2 normalization technique for normalization processor. Essentially L2 norm is "score" divided by square root of sum of score squares (more details here). Example of pipeline with processor config:
Issues Resolved
#228, part of solution for #126
Check List
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