Observation Update
https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations/OBSERVATION_ID
Request Method: PUT
Name | Type | Required? | Description |
---|---|---|---|
assignments | N | Provide suggestion or assignments . Only provide if you want to manually specify values that the parameters held during this trial. | |
failed | boolean | N | A boolean indicating whether this observation failed for some reason. SigOpt takes this into consideration when optimizing. It is invalid for both failed to be true , and value to be present. The default value is false . |
metadata | N | Optional user-provided object. See Using Metadata for more information. | |
suggestion | string | N | |
values | N | An array of Metric Evaluation objects. For experiments with more than one Metric, you must use this instead of value and value_stddev . |
These parameters should no longer be used because there are better alternatives.
Name | Type | Required? | Description |
---|---|---|---|
value | float | N | The observed metric value from this trial. |
value_stddev | float | N | The standard deviation in value that was observed in this trial. |
Python
Bash
Java
observation = conn.experiments(EXPERIMENT_ID).observations(OBSERVATION_ID).update(
values=[
dict(
name="Accuracy",
value=1,
value_stddev=0.1
)
]
)
OBSERVATION=`curl -s -X PUT https://api.sigopt.com/v1/experiments/EXPERIMENT_ID/observations/OBSERVATION_ID -u "$SIGOPT_API_TOKEN": \
-H 'Content-Type: application/json' \
-d "{\"values\":[{\"name\":\"Accuracy\",\"value\":1,\"value_stddev\":0.1}]}"`
Observation observation = new Experiment(EXPERIMENT_ID).observations(OBSERVATION_ID).update()
data(
new Observation.Builder()
.suggestion("1")
.values(java.util.Arrays.asList(
new Value.Builder()
.name("Accuracy")
.value(1)
.valueStddev(0.1)
.build()
))
.build()
)
.call();
{
"assignments": {
"degree": 2,
"gamma": 3.6,
"kernel": "rbf"
},
"created": 1414800000,
"experiment": "1",
"failed": false,
"id": "4",
"metadata": null,
"object": "observation",
"suggestion": "1",
"value": 1,
"value_stddev": 0.1,
"values": [
{
"name": "Accuracy",
"object": "metric_evaluation",
"value": 1,
"value_stddev": 0.1
}
]
}
Last modified 6mo ago