mirror of
https://github.com/honeymoose/OpenSearch.git
synced 2025-02-05 20:48:22 +00:00
2171b6b47f
This PR adds the resource documentation of the data frame analytics APIs and the evaluate API to the ML API doc pool.
63 lines
2.2 KiB
Plaintext
63 lines
2.2 KiB
Plaintext
[role="xpack"]
|
|
[testenv="platinum"]
|
|
[[ml-evaluate-dfanalytics-resources]]
|
|
=== {dfanalytics-cap} evaluation resources
|
|
|
|
Evaluation configuration objects relate to the <<evaluate-dfanalytics>>.
|
|
|
|
[discrete]
|
|
[[ml-evaluate-dfanalytics-properties]]
|
|
==== {api-definitions-title}
|
|
|
|
`evaluation`::
|
|
(object) Defines the type of evaluation you want to perform. The value of this
|
|
object can be different depending on the type of evaluation you want to
|
|
perform. For example, it can contain <<binary-sc-resources>>.
|
|
|
|
[[binary-sc-resources]]
|
|
==== Binary soft classification configuration objects
|
|
|
|
Binary soft classification evaluates the results of an analysis which outputs
|
|
the probability that each {dataframe} row belongs to a certain class. For
|
|
example, in the context of outlier detection, the analysis outputs the
|
|
probability whether each row is an outlier.
|
|
|
|
[discrete]
|
|
[[binary-sc-resources-properties]]
|
|
===== {api-definitions-title}
|
|
|
|
`actual_field`::
|
|
(string) The field of the `index` which contains the `ground
|
|
truth`. The data type of this field can be boolean or integer. If the data
|
|
type is integer, the value has to be either `0` (false) or `1` (true).
|
|
|
|
`predicted_probability_field`::
|
|
(string) The field of the `index` that defines the probability of whether the
|
|
item belongs to the class in question or not. It's the field that contains the
|
|
results of the analysis.
|
|
|
|
`metrics`::
|
|
(object) Specifies the metrics that are used for the evaluation. Available
|
|
metrics:
|
|
|
|
`auc_roc`::
|
|
(object) The AUC ROC (area under the curve of the receiver operating
|
|
characteristic) score and optionally the curve.
|
|
Default value is {"includes_curve": false}.
|
|
|
|
`precision`::
|
|
(object) Set the different thresholds of the {olscore} at where the metric
|
|
is calculated.
|
|
Default value is {"at": [0.25, 0.50, 0.75]}.
|
|
|
|
`recall`::
|
|
(object) Set the different thresholds of the {olscore} at where the metric
|
|
is calculated.
|
|
Default value is {"at": [0.25, 0.50, 0.75]}.
|
|
|
|
`confusion_matrix`::
|
|
(object) Set the different thresholds of the {olscore} at where the metrics
|
|
(`tp` - true positive, `fp` - false positive, `tn` - true negative, `fn` -
|
|
false negative) are calculated.
|
|
Default value is {"at": [0.25, 0.50, 0.75]}.
|
|
|