Machine Learning Forecast¶

Get the predition results of the deployed machine learning algorithm model.

Request Format¶

POST https://{apigw-address}/ml-service/v1.0/forecasts?action=run&orgId={}&serviceId={}

Request Parameters (URI)¶

Name	Location (Path/Query)	Required or Not	Data Type	Description
orgId	Query	true	String	Organization ID which the user belongs to. How to get orgId >>
serviceId	Query	true	String	Service ID that is generated after deploying the algorithm model. How to get serviceId >>

Request Parameters (Body)¶

Name	Required or Not	Data Type	Description
parameters	true	String	Business parameters for the algorithm model in JSON format. The parameters and values must match with the requirement of the model.

Response Parameters¶

Name	Data Type	Description
data	Object(String)	Returned prediction results in JSON format. Data type of the results can be basic data types, complex types, and array.

Sample 1¶

Request Sample¶

url: https://{apigw-address}/ml-service/v1.0/forecasts?action=run&orgId=o15475450989191&serviceId=f40fbb09-ce20-463f-bb18

method: POST

requestBody:
{
    "parameters":{
"ColumnNames": [
        "age",
        "workclass",
        "fnlwgt",
        "education",
        "education-num",
        "marital-status",
        "occupation",
        "relationship",
        "race",
        "sex",
        "capital-gain",
        "capital-loss",
        "hours-per-week",
        "native-country"
      ],
      "Values": [
        [
          "0",
          "value",
          "0",
          "value",
          "0",
          "value",
          "value",
          "value",
          "value",
          "value",
          "0",
          "0",
          "0",
          "value"
        ],
        [
          "0",
          "value",
          "0",
          "value",
          "0",
          "value",
          "value",
          "value",
          "value",
          "value",
          "0",
          "0",
          "0",
          "value"
        ]
      ]
 }
}

Return Sample¶

{
  "status": 0,
  "msg": "Success",
  "data": {
        "ColumnNames": [
          "Scored Labels",
          "Scored Probabilities"
        ],
        "ColumnTypes": [
          "String",
          "Numeric"
        ],
        "Values": [
          [
            "value",
            "0"
          ],
          [
            "value",
            "0"
          ]
        ]
  }
}