Retrieve predictive scoring model

Request

Retrieve a specific predictive scoring model's statistics.

Security

TdApikeyAuth

Path

audienceIdinteger, (int64)required

predictiveSegmentIdinteger, (int64)required

curl -i -X GET \
  'https://api-cdp.treasuredata.com/audiences/{audienceId}/predictive_segments/{predictiveSegmentId}' \
  -H 'Authorization: YOUR_API_KEY_HERE'

Responses

success

Bodyapplication/json

audienceIdstring, (integer)

idstring, (integer)

baseSegmentIdstring or null, (integer)

segmentIdstring, (integer)

scoredSegmentIdstring or null, (integer)

namestring

descriptionstring or null

categoricalAsColumnNamesArray of strings

categoricalArrayAsColumnNamesArray of strings

quantitativeAsColumnNamesArray of strings

accuracynumber or null, (double), [ 0 .. 100 ](PredictiveSegmentAccuracy)

Accuracy for trained model evaluated on initial training.

areaUnderRocCurvenumber or null, (double), [ 0 .. 1 ](PredictiveSegmentAreaUnderRocCurve)

Evaluation score for the model. See also https://en.wikipedia.org/wiki/Receiver_operating_characteristic#Area_under_the_curve

gradeThresholdsArray of numbers, = 3 items(PredictiveSegmentGradeThresholds)

Given the items [a, b, c], they must meet the condition a >= b >= c

Example:

createdAtstring, (date-time)

updatedAtstring, (date-time)

Response

{
  "audienceId": "string",
  "id": "string",
  "baseSegmentId": "string",
  "segmentId": "string",
  "scoredSegmentId": "string",
  "name": "string",
  "description": "string",
  "categoricalAsColumnNames": [
    "string"
  ],
  "categoricalArrayAsColumnNames": [
    "string"
  ],
  "quantitativeAsColumnNames": [
    "string"
  ],
  "accuracy": 0,
  "areaUnderRocCurve": 0,
  "gradeThresholds": [
    75,
    50,
    25
  ],
  "createdAt": "2019-08-24T14:15:22Z",
  "updatedAt": "2019-08-24T14:15:22Z"
}