IMPORTANT: No additional bug fixes or documentation updates
will be released for this version. For the latest information, see the
current release documentation.
Preview data frame analytics API
editPreview data frame analytics API
editPreviews the features used by a data frame analytics config.
Request
editGET _ml/data_frame/analytics/_preview
POST _ml/data_frame/analytics/_preview
GET _ml/data_frame/analytics/<data_frame_analytics_id>/_preview
POST _ml/data_frame/analytics/<data_frame_analytics_id>/_preview
Prerequisites
editRequires the monitor_ml cluster privilege. This privilege is included in the
machine_learning_user built-in role.
Description
editThis API provides preview of the extracted features for a data frame analytics config that either exists already or one that has not been created yet.
Path parameters
edit-
<data_frame_analytics_id> - (Optional, string) Identifier for the data frame analytics job.
Request body
edit-
config -
(Optional, object)
A data frame analytics config as described in Create data frame analytics jobs.
Note that
idanddestdon’t need to be provided in the context of this API.
Response body
editThe API returns a response that contains the following:
-
feature_values - (array) An array of objects that contain feature name and value pairs. The features have been processed and indicate what will be sent to the model for training.
Examples
editresp = client.ml.preview_data_frame_analytics(
config={
"source": {
"index": "houses_sold_last_10_yrs"
},
"analysis": {
"regression": {
"dependent_variable": "price"
}
}
},
)
print(resp)
const response = await client.ml.previewDataFrameAnalytics({
config: {
source: {
index: "houses_sold_last_10_yrs",
},
analysis: {
regression: {
dependent_variable: "price",
},
},
},
});
console.log(response);
POST _ml/data_frame/analytics/_preview
{
"config": {
"source": {
"index": "houses_sold_last_10_yrs"
},
"analysis": {
"regression": {
"dependent_variable": "price"
}
}
}
}
The API returns the following results:
{
"feature_values": [
{
"number_of_bedrooms": "1",
"postcode": "29655",
"price": "140.4"
},
...
]
}