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Request service cycle training
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Available in Classic and VPC
Request that a service with a service type of interval
train a dataset periodically.
Request
The following describes the request format for the endpoint. The request format is as follows:
Method | URI |
---|---|
PUT | /services/{serviceId}/schedule |
Request headers
For headers common to all AiTEMS APIs, see Common AiTEMS headers.
Request path parameters
The following describes the parameters.
Field | Type | Required | Description |
---|---|---|---|
serviceId | String | Required | Service ID
|
Request query parameters
The following describes the parameters.
Field | Type | Required | Description |
---|---|---|---|
action | String | Required | Whether to run cycle training
|
Request body
The following describes the request body.
Field | Type | Required | Description |
---|---|---|---|
trainTypes | Array | Required | Training request type
|
description | String | Optional | Training description |
hpConfig | Object | Required | Hyperparameter optimization (HPO) settings information |
hpConfig.is_enabled | Boolean | Required | HPO configuration status
|
hpConfig.{option} | String, Long, Boolean | Optional | Configured HPO value
|
HPO
The following describes the configurable HPO values.
Option name | Type | Required | Training type | Description |
---|---|---|---|---|
session_max_timestamp | Long | Optional | Personalized recommendations, related item recommendations | Maximum idle time (in seconds) between actions to consider the same session
|
item_top_n | Long | Optional | Personalized recommendations, related item recommendations | Maximum number of products to be used for recommendations
|
min_item_cut | Long | Optional | Personalized recommendations, related item recommendations | Product minimum appearance count
|
min_session_length | Long | Optional | Personalized recommendations, related item recommendations | Minimum number of actions in a session
|
max_user_recommend_top | Long | Optional | Personalized recommendation | Maximum number of recommendations per user
|
max_relate_recommend_top | Long | Optional | Related item recommendation | Maximum number of related item recommendations per product
|
remove_history_item | Boolean | Optional | Personalized recommendations, related item recommendations | Whether to remove previously recommended products from personalized recommendations list
|
group_column | Array | Required | Popular item recommendation | List of popular extract group columns
|
target_column | String | Optional | Popular item recommendation | Popular extract target columns
|
max_group_recommend_top | Long | Optional | Popular item recommendation | Maximum number of popular products per group
|
Request example
The following is a sample request.
curl --location --request PUT 'https://aitems.apigw.ntruss.com/api/v1/services/6wxgu******/schedule
?action=start' \
--header 'x-ncp-apigw-timestamp: {Timestamp}' \
--header 'x-ncp-iam-access-key: {Access Key}' \
--header 'x-ncp-apigw-signature-v2: {API Gateway Signature}' \
--header 'Content-Type: application/json' \
--data '{
"trainTypes": [
"pop"
],
"hpConfig": {
"is_enabled": false
}
}'
Response
The following describes the response format.
Response body
The following describes the response body.
Field | Type | Required | Description |
---|---|---|---|
serviceId | String | - | Service ID |
name | String | - | Service name |
description | String | - | Service description |
status | String | - | Service status
|
datasets | Array | - | Information of dataset set to service |
hpConfig | Object | - | Hyperparameter optimization (HPO) settings information |
hpConfig.is_enabled | Boolean | - | HPO configuration status
|
hpConfig.{option} | String, Long, Boolean | - | Configured HPO value
|
infers | Array | - | Training result information
|
createdDate | String | - | Service creation date and time |
updatedDate | String | - | Last update date and time of the service |
type | String | - | Service type
|
learningInterval | String | - | Dataset update cycle |
scheduledDate | String | - | Dataset update scheduling time |
datasets
The following describes datasets
.
Field | Type | Required | Description |
---|---|---|---|
datasetId | String | - | Dataset ID set to the service |
type | String | - | Dataset type set to the service
|
name | String | - | Dataset name set to the service |
schemaName | String | - | Dataset schema name set to the service |
status | String | - | Status of dataset set to the service
|
createdDate | String | - | Creation date and time of dataset set to the service |
updatedDate | String | - | Last update date and time of dataset set to the service |
infers
The following describes infers
.
Field | Type | Required | Description |
---|---|---|---|
dataType | String | - | Dataset type of training result
|
trainVersion | String | - | Training result version |
status | String | - | Training result status
|
rowCount | String | - | Result data count |
createdDate | String | - | Data creation date and time |
updatedDate | String | - | Last update date and time of data |
Response status codes
For response status codes common to all AiTEMS APIs, see Common AiTEMS API response status codes.
Response example
The following is a sample example.
{
"serviceId": "6wxgu******",
"name": "service2",
"description": "",
"status": "scheduled",
"datasets": [
{
"datasetId": "bu457******",
"type": "interaction",
"name": "interaction_dataset",
"schemaName": "interaction_schema",
"status": "learnable",
"createdDate": "2024-07-30T09:49:19.254",
"updatedDate": "2024-07-30T09:49:35.364"
},
{
"datasetId": "g8rf6******",
"type": "item",
"name": "item_dataset",
"schemaName": "item_schema",
"status": "learnable",
"createdDate": "2024-07-29T16:46:35.968",
"updatedDate": "2024-07-30T08:57:35.209"
},
{
"datasetId": "oeq4i******",
"type": "user",
"name": "user_dataset",
"schemaName": "user_schema",
"status": "learnable",
"createdDate": "2024-07-30T08:58:00.662",
"updatedDate": "2024-07-30T08:58:35.205"
}
],
"hpConfig": {
"is_enabled": false
},
"infers": [],
"createdDate": "2024-07-30T10:28:57.825",
"updatedDate": "2024-07-30T10:29:21.550",
"type": "interval",
"learningInterval": "hour1",
"scheduledDate": "2024-07-30T11:25:36.558"
}