REQUIRED |
KEY |
TYPE |
DESCRIPTION |
Yes |
deploymentToken |
str |
The deployment token to authenticate access to created deployments. This token is only authorized to predict on deployments in this project, so it is safe to embed this model within an application or website.
|
Yes |
deploymentId |
str |
The unique identifier for a deployment created under the project.
|
Yes |
queryData |
dict |
A dictionary where the 'Key' is the column name (e.g. a column with the name 'user_id' in your dataset) mapped to the column mapping USER_ID that uniquely identifies the entity against which a prediction is performed and the 'Value' is the unique value of the same entity.
|
No |
threshold |
float |
A float value that is applied on the popular class label.
|
No |
thresholdClass |
str |
The label upon which the threshold is added (binary labels only).
|
No |
thresholds |
dict |
Maps labels to thresholds (multi-label classification only). Defaults to F1 optimal threshold if computed for the given class, else uses 0.5.
|
No |
explainPredictions |
bool |
If True, returns the SHAP explanations for all input features.
|
No |
fixedFeatures |
list |
A set of input features to treat as constant for explanations - only honored when the explainer type is KERNEL_EXPLAINER
|
No |
nested |
str |
If specified generates prediction delta for each index of the specified nested feature.
|
No |
explainerType |
str |
The type of explainer to use.
|
Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.