Comments (4)
ranklib_standalone_test.tar.gz
from elasticsearch-learning-to-rank.
I was similarly puzzled, but when I run the query below, I get two docs with a score of 1.0, not the field value I expected. When documents are missing a feature, they get a vaue of 0.0. So all 3 would take the left split
GET /rando/_search
{
"query": {
"script": {
"script": {
"lang": "expression",
"inline": "doc['lucky_number']"
}
}
}
}
from elasticsearch-learning-to-rank.
Using a function_score_query
with a field value factor works:
GET /rando/_search
{
"query": {
"ltr": {
"model": {
"stored": "testmodel"
},
"features": [
{
"function_score": {
"query": {
"match_all": {}
},
"functions": [
{
"field_value_factor": {
"field": "lucky_number"
}
}
]
}
}
]
}
},
"script_fields": {
"1": {
"script": {
"lang": "expression",
"inline": "doc['lucky_number']"
}
}
},
"_source": true
}
from elasticsearch-learning-to-rank.
Awesome. Better RTFD prevailed! Thanks.
from elasticsearch-learning-to-rank.
Related Issues (20)
- Update elasticsearch to 7.17.5 HOT 3
- elasticsearch-learning-to-rank plugin for ES 8.x HOT 3
- ES 6.8.23 -> LTR Build Request HOT 9
- Cannot Install Plugin HOT 2
- Plans for a similar opensearch plugin? HOT 1
- not able to install ETL Plugin into Ubuntu Server 22.04 LTS HOT 1
- Update elasticsearch to 8.5.1
- Update elasticsearch to 8.5.2
- LTR for Elasticsearch 8.4.1 HOT 1
- There is no release for elasticsearch 7.17.9 HOT 3
- How is the final score of a LambdaMart model calculated?
- How to include categorical features in feature set HOT 5
- Dense Vector Feature as a param to a Mustache script score template HOT 2
- Using LTR together with the Go Typed-API Client?
- Search Keyword with certain conditions HOT 2
- Recent versions are not published to Maven repository HOT 1
- sltr queries with minimum_should_match features
- Implement support for missing values with XGBoost
- Flaky test testLogExtraLogging fails occasionally HOT 1
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from elasticsearch-learning-to-rank.