SegmentML
SegmentML Model Fetch
Get a SegmentML model.
Additional atttributes from a completed SegmentML model GET response:
| field | DataType | Description |
|---|---|---|
| features: kind | string | The field is either a Lytics Segment feature (segment), a lql/user-field feature (lql), a Lytics Behavioral Score feature (score), or a Lytics Content Affinity feature (content) |
| features: fieldtype | string | Field type is either numeric or categorical |
| features: name | string | The name of a field |
| features: importance | number | The relative importance of a field in the model |
| features: correlation | number | Correlation between specific field and target |
| features: impact | object | The impact object details the Lift and shows the marginal effect of a feature on the predicted outcome of the model |
| mse | number | Mean-squared error value |
| rsq | number | R-squared value or coefficient of determination |
| false_negative | number | The number of users in the source segment who are predicted to be in the target segment. |
| false_positive | number | The number of users in the target segment who are not predicted to be in the target segment. |
| true_negative | number | The number of users in the source segment who are not predicted to be in the target segment. |
| true_positive | number | The number of users in the target segment who are predicted to be in the target segment. |
| success | []number | Number of successful predictions for a given prediction value |
| failure | []number | Number of failed predictions for a given prediction value |
| auc | number | Area under the ROC curve |
| threshold | number | Optimal decision threshold to minimize false-positives and false-negatives |
| accuracy | number | A value that represents the accuracy of the model; scale ranges from 0 (least accurate) to 10 (most accurate). |
| reach | number | A value that represents the number of source users that look like target users; scale ranges from 0 (low reach) to 10 (high reach). |
| model_health | number | The overall health of the model (i.e. "healthy", "unhealthy") |
| msgs | number | Messages for the user about the model with levels of severity (i.e. "debug", "info", "warn", "error") |
To learn more about the metrics false negative, false positive etc., check out binary classification.
# Curl example of getting a SegmentML model
curl -s -J -XGET "https://api.lytics.io/api/segmentml/all::smt_power" -H "Authorization: $LIOKEY"
get/api/segmentml/{id}
Request
- Base URLhttps://api.lytics.io
- URLhttps://api.lytics.io/api/segmentml/{id}
- AuthAPI key in header Authorization
Path parameters
idstring required
ID of the SegmentML model to retrieve, of the form SOURCE_SLUG::TARGET_SLUG.
Query parameters
account_idstring
Your Lytics account ID.
Response
OK
Changes
No recorded changes to this operation across all 1 revision of this API.