github-mirrors/elasticsearch
1
0
Fork 0
mirror of https://github.com/elastic/elasticsearch.git synced 2025-04-24 23:27:25 -04:00
Code Issues Projects Releases Packages Wiki Activity

Allow the user to specify 'query' in Evaluate Data Frame request (#45775)

Browse source
This commit is contained in:
Przemysław Witek 2019-08-22 08:27:38 +02:00 • committed by GitHub
parent 3cf174d239
commit 31f6e78acd
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
19 changed files with 414 additions and 108 deletions
Download patch file Download diff file Expand all files Collapse all files

17
docs/java-rest/high-level/ml/evaluate-data-frame.asciidoc
View file

@ -18,14 +18,15 @@ include-tagged::{doc-tests-file}[{api}-request]
--------------------------------------------------
<1> Constructing a new evaluation request
<2> Reference to an existing index
<3> Kind of evaluation to perform
<4> Name of the field in the index. Its value denotes the actual (i.e. ground truth) label for an example. Must be either true or false
<5> Name of the field in the index. Its value denotes the probability (as per some ML algorithm) of the example being classified as positive
<6> The remaining parameters are the metrics to be calculated based on the two fields described above.
<7> https://en.wikipedia.org/wiki/Precision_and_recall[Precision] calculated at thresholds: 0.4, 0.5 and 0.6
<8> https://en.wikipedia.org/wiki/Precision_and_recall[Recall] calculated at thresholds: 0.5 and 0.7
<9> https://en.wikipedia.org/wiki/Confusion_matrix[Confusion matrix] calculated at threshold 0.5
<10> https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve[AuC ROC] calculated and the curve points returned
<3> The query with which to select data from indices
<4> Kind of evaluation to perform
<5> Name of the field in the index. Its value denotes the actual (i.e. ground truth) label for an example. Must be either true or false
<6> Name of the field in the index. Its value denotes the probability (as per some ML algorithm) of the example being classified as positive
<7> The remaining parameters are the metrics to be calculated based on the two fields described above.
<8> https://en.wikipedia.org/wiki/Precision_and_recall[Precision] calculated at thresholds: 0.4, 0.5 and 0.6
<9> https://en.wikipedia.org/wiki/Precision_and_recall[Recall] calculated at thresholds: 0.5 and 0.7
<10> https://en.wikipedia.org/wiki/Confusion_matrix[Confusion matrix] calculated at threshold 0.5
<11> https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve[AuC ROC] calculated and the curve points returned
include::../execution.asciidoc[]