Struct aws_sdk_machinelearning::model::evaluation::Builder
source · [−]#[non_exhaustive]pub struct Builder { /* private fields */ }
Expand description
A builder for Evaluation
Implementations
sourceimpl Builder
impl Builder
sourcepub fn evaluation_id(self, input: impl Into<String>) -> Self
pub fn evaluation_id(self, input: impl Into<String>) -> Self
The ID that is assigned to the Evaluation
at creation.
sourcepub fn set_evaluation_id(self, input: Option<String>) -> Self
pub fn set_evaluation_id(self, input: Option<String>) -> Self
The ID that is assigned to the Evaluation
at creation.
sourcepub fn ml_model_id(self, input: impl Into<String>) -> Self
pub fn ml_model_id(self, input: impl Into<String>) -> Self
The ID of the MLModel
that is the focus of the evaluation.
sourcepub fn set_ml_model_id(self, input: Option<String>) -> Self
pub fn set_ml_model_id(self, input: Option<String>) -> Self
The ID of the MLModel
that is the focus of the evaluation.
sourcepub fn evaluation_data_source_id(self, input: impl Into<String>) -> Self
pub fn evaluation_data_source_id(self, input: impl Into<String>) -> Self
The ID of the DataSource
that is used to evaluate the MLModel
.
sourcepub fn set_evaluation_data_source_id(self, input: Option<String>) -> Self
pub fn set_evaluation_data_source_id(self, input: Option<String>) -> Self
The ID of the DataSource
that is used to evaluate the MLModel
.
sourcepub fn input_data_location_s3(self, input: impl Into<String>) -> Self
pub fn input_data_location_s3(self, input: impl Into<String>) -> Self
The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
sourcepub fn set_input_data_location_s3(self, input: Option<String>) -> Self
pub fn set_input_data_location_s3(self, input: Option<String>) -> Self
The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
sourcepub fn created_by_iam_user(self, input: impl Into<String>) -> Self
pub fn created_by_iam_user(self, input: impl Into<String>) -> Self
The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.
sourcepub fn set_created_by_iam_user(self, input: Option<String>) -> Self
pub fn set_created_by_iam_user(self, input: Option<String>) -> Self
The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS Identity and Access Management (IAM) user account.
sourcepub fn created_at(self, input: DateTime) -> Self
pub fn created_at(self, input: DateTime) -> Self
The time that the Evaluation
was created. The time is expressed in epoch time.
sourcepub fn set_created_at(self, input: Option<DateTime>) -> Self
pub fn set_created_at(self, input: Option<DateTime>) -> Self
The time that the Evaluation
was created. The time is expressed in epoch time.
sourcepub fn last_updated_at(self, input: DateTime) -> Self
pub fn last_updated_at(self, input: DateTime) -> Self
The time of the most recent edit to the Evaluation
. The time is expressed in epoch time.
sourcepub fn set_last_updated_at(self, input: Option<DateTime>) -> Self
pub fn set_last_updated_at(self, input: Option<DateTime>) -> Self
The time of the most recent edit to the Evaluation
. The time is expressed in epoch time.
sourcepub fn name(self, input: impl Into<String>) -> Self
pub fn name(self, input: impl Into<String>) -> Self
A user-supplied name or description of the Evaluation
.
sourcepub fn set_name(self, input: Option<String>) -> Self
pub fn set_name(self, input: Option<String>) -> Self
A user-supplied name or description of the Evaluation
.
sourcepub fn status(self, input: EntityStatus) -> Self
pub fn status(self, input: EntityStatus) -> Self
The status of the evaluation. This element can have one of the following values:
-
PENDING
- Amazon Machine Learning (Amazon ML) submitted a request to evaluate anMLModel
. -
INPROGRESS
- The evaluation is underway. -
FAILED
- The request to evaluate anMLModel
did not run to completion. It is not usable. -
COMPLETED
- The evaluation process completed successfully. -
DELETED
- TheEvaluation
is marked as deleted. It is not usable.
sourcepub fn set_status(self, input: Option<EntityStatus>) -> Self
pub fn set_status(self, input: Option<EntityStatus>) -> Self
The status of the evaluation. This element can have one of the following values:
-
PENDING
- Amazon Machine Learning (Amazon ML) submitted a request to evaluate anMLModel
. -
INPROGRESS
- The evaluation is underway. -
FAILED
- The request to evaluate anMLModel
did not run to completion. It is not usable. -
COMPLETED
- The evaluation process completed successfully. -
DELETED
- TheEvaluation
is marked as deleted. It is not usable.
sourcepub fn performance_metrics(self, input: PerformanceMetrics) -> Self
pub fn performance_metrics(self, input: PerformanceMetrics) -> Self
Measurements of how well the MLModel
performed, using observations referenced by the DataSource
. One of the following metrics is returned, based on the type of the MLModel
:
-
BinaryAUC: A binary
MLModel
uses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: A regression
MLModel
uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. -
MulticlassAvgFScore: A multiclass
MLModel
uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
sourcepub fn set_performance_metrics(self, input: Option<PerformanceMetrics>) -> Self
pub fn set_performance_metrics(self, input: Option<PerformanceMetrics>) -> Self
Measurements of how well the MLModel
performed, using observations referenced by the DataSource
. One of the following metrics is returned, based on the type of the MLModel
:
-
BinaryAUC: A binary
MLModel
uses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: A regression
MLModel
uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable. -
MulticlassAvgFScore: A multiclass
MLModel
uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
sourcepub fn message(self, input: impl Into<String>) -> Self
pub fn message(self, input: impl Into<String>) -> Self
A description of the most recent details about evaluating the MLModel
.
sourcepub fn set_message(self, input: Option<String>) -> Self
pub fn set_message(self, input: Option<String>) -> Self
A description of the most recent details about evaluating the MLModel
.
sourcepub fn compute_time(self, input: i64) -> Self
pub fn compute_time(self, input: i64) -> Self
Long integer type that is a 64-bit signed number.
sourcepub fn set_compute_time(self, input: Option<i64>) -> Self
pub fn set_compute_time(self, input: Option<i64>) -> Self
Long integer type that is a 64-bit signed number.
sourcepub fn finished_at(self, input: DateTime) -> Self
pub fn finished_at(self, input: DateTime) -> Self
A timestamp represented in epoch time.
sourcepub fn set_finished_at(self, input: Option<DateTime>) -> Self
pub fn set_finished_at(self, input: Option<DateTime>) -> Self
A timestamp represented in epoch time.
sourcepub fn started_at(self, input: DateTime) -> Self
pub fn started_at(self, input: DateTime) -> Self
A timestamp represented in epoch time.
sourcepub fn set_started_at(self, input: Option<DateTime>) -> Self
pub fn set_started_at(self, input: Option<DateTime>) -> Self
A timestamp represented in epoch time.
sourcepub fn build(self) -> Evaluation
pub fn build(self) -> Evaluation
Consumes the builder and constructs a Evaluation
Trait Implementations
impl StructuralPartialEq for Builder
Auto Trait Implementations
impl RefUnwindSafe for Builder
impl Send for Builder
impl Sync for Builder
impl Unpin for Builder
impl UnwindSafe for Builder
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcepub fn borrow_mut(&mut self) -> &mut T
pub fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<T> Instrument for T
impl<T> Instrument for T
sourcefn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
sourcefn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcepub fn to_owned(&self) -> T
pub fn to_owned(&self) -> T
Creates owned data from borrowed data, usually by cloning. Read more
sourcepub fn clone_into(&self, target: &mut T)
pub fn clone_into(&self, target: &mut T)
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more
sourceimpl<T> WithSubscriber for T
impl<T> WithSubscriber for T
sourcefn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
sourcefn with_current_subscriber(self) -> WithDispatch<Self>
fn with_current_subscriber(self) -> WithDispatch<Self>
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more