| Copyright | (c) 2013-2023 Brendan Hay |
|---|---|
| License | Mozilla Public License, v. 2.0. |
| Maintainer | Brendan Hay |
| Stability | auto-generated |
| Portability | non-portable (GHC extensions) |
| Safe Haskell | Safe-Inferred |
| Language | Haskell2010 |
Amazonka.MachineLearning.UpdateMLModel
Description
Updates the MLModelName and the ScoreThreshold of an MLModel.
You can use the GetMLModel operation to view the contents of the
updated data element.
Synopsis
- data UpdateMLModel = UpdateMLModel' {}
- newUpdateMLModel :: Text -> UpdateMLModel
- updateMLModel_mLModelName :: Lens' UpdateMLModel (Maybe Text)
- updateMLModel_scoreThreshold :: Lens' UpdateMLModel (Maybe Double)
- updateMLModel_mLModelId :: Lens' UpdateMLModel Text
- data UpdateMLModelResponse = UpdateMLModelResponse' {
- mLModelId :: Maybe Text
- httpStatus :: Int
- newUpdateMLModelResponse :: Int -> UpdateMLModelResponse
- updateMLModelResponse_mLModelId :: Lens' UpdateMLModelResponse (Maybe Text)
- updateMLModelResponse_httpStatus :: Lens' UpdateMLModelResponse Int
Creating a Request
data UpdateMLModel Source #
See: newUpdateMLModel smart constructor.
Constructors
| UpdateMLModel' | |
Fields
| |
Instances
Arguments
| :: Text | |
| -> UpdateMLModel |
Create a value of UpdateMLModel with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
$sel:mLModelName:UpdateMLModel', updateMLModel_mLModelName - A user-supplied name or description of the MLModel.
UpdateMLModel, updateMLModel_scoreThreshold - The ScoreThreshold used in binary classification MLModel that marks
the boundary between a positive prediction and a negative prediction.
Output values greater than or equal to the ScoreThreshold receive a
positive result from the MLModel, such as true. Output values less
than the ScoreThreshold receive a negative response from the
MLModel, such as false.
UpdateMLModel, updateMLModel_mLModelId - The ID assigned to the MLModel during creation.
Request Lenses
updateMLModel_mLModelName :: Lens' UpdateMLModel (Maybe Text) Source #
A user-supplied name or description of the MLModel.
updateMLModel_scoreThreshold :: Lens' UpdateMLModel (Maybe Double) Source #
The ScoreThreshold used in binary classification MLModel that marks
the boundary between a positive prediction and a negative prediction.
Output values greater than or equal to the ScoreThreshold receive a
positive result from the MLModel, such as true. Output values less
than the ScoreThreshold receive a negative response from the
MLModel, such as false.
updateMLModel_mLModelId :: Lens' UpdateMLModel Text Source #
The ID assigned to the MLModel during creation.
Destructuring the Response
data UpdateMLModelResponse Source #
Represents the output of an UpdateMLModel operation.
You can see the updated content by using the GetMLModel operation.
See: newUpdateMLModelResponse smart constructor.
Constructors
| UpdateMLModelResponse' | |
Fields
| |
Instances
newUpdateMLModelResponse Source #
Create a value of UpdateMLModelResponse with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
UpdateMLModel, updateMLModelResponse_mLModelId - The ID assigned to the MLModel during creation. This value should be
identical to the value of the MLModelID in the request.
$sel:httpStatus:UpdateMLModelResponse', updateMLModelResponse_httpStatus - The response's http status code.
Response Lenses
updateMLModelResponse_mLModelId :: Lens' UpdateMLModelResponse (Maybe Text) Source #
The ID assigned to the MLModel during creation. This value should be
identical to the value of the MLModelID in the request.
updateMLModelResponse_httpStatus :: Lens' UpdateMLModelResponse Int Source #
The response's http status code.