[−][src]Struct rusoto_machinelearning::Evaluation
Represents the output of GetEvaluation
operation.
The content consists of the detailed metadata and data file information and the current status of the Evaluation
.
Fields
compute_time: Option<i64>
created_at: Option<f64>
The time that the Evaluation
was created. The time is expressed in epoch time.
created_by_iam_user: Option<String>
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.
evaluation_data_source_id: Option<String>
The ID of the DataSource
that is used to evaluate the MLModel
.
evaluation_id: Option<String>
The ID that is assigned to the Evaluation
at creation.
finished_at: Option<f64>
input_data_location_s3: Option<String>
The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
last_updated_at: Option<f64>
The time of the most recent edit to the Evaluation
. The time is expressed in epoch time.
ml_model_id: Option<String>
The ID of the MLModel
that is the focus of the evaluation.
message: Option<String>
A description of the most recent details about evaluating the MLModel
.
name: Option<String>
A user-supplied name or description of the Evaluation
.
performance_metrics: Option<PerformanceMetrics>
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.
started_at: Option<f64>
status: Option<String>
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.
Trait Implementations
impl Default for Evaluation
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impl Default for Evaluation
fn default() -> Evaluation
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fn default() -> Evaluation
Returns the "default value" for a type. Read more
impl PartialEq<Evaluation> for Evaluation
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impl PartialEq<Evaluation> for Evaluation
fn eq(&self, other: &Evaluation) -> bool
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fn eq(&self, other: &Evaluation) -> bool
This method tests for self
and other
values to be equal, and is used by ==
. Read more
fn ne(&self, other: &Evaluation) -> bool
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fn ne(&self, other: &Evaluation) -> bool
This method tests for !=
.
impl Clone for Evaluation
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impl Clone for Evaluation
fn clone(&self) -> Evaluation
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fn clone(&self) -> Evaluation
Returns a copy of the value. Read more
fn clone_from(&mut self, source: &Self)
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fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source
. Read more
impl Debug for Evaluation
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impl Debug for Evaluation
fn fmt(&self, f: &mut Formatter) -> Result
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fn fmt(&self, f: &mut Formatter) -> Result
Formats the value using the given formatter. Read more
impl<'de> Deserialize<'de> for Evaluation
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impl<'de> Deserialize<'de> for Evaluation
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
Auto Trait Implementations
impl Send for Evaluation
impl Send for Evaluation
impl Sync for Evaluation
impl Sync for Evaluation
Blanket Implementations
impl<T, U> Into for T where
U: From<T>,
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impl<T, U> Into for T where
U: From<T>,
impl<T> ToOwned for T where
T: Clone,
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impl<T> ToOwned for T where
T: Clone,
type Owned = T
fn to_owned(&self) -> T
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fn to_owned(&self) -> T
Creates owned data from borrowed data, usually by cloning. Read more
fn clone_into(&self, target: &mut T)
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fn clone_into(&self, target: &mut T)
🔬 This is a nightly-only experimental API. (toowned_clone_into
)
recently added
Uses borrowed data to replace owned data, usually by cloning. Read more
impl<T> From for T
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impl<T> From for T
impl<T, U> TryFrom for T where
T: From<U>,
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impl<T, U> TryFrom for T where
T: From<U>,
type Error = !
try_from
)The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
try_from
)Performs the conversion.
impl<T> Borrow for T where
T: ?Sized,
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impl<T> Borrow for T where
T: ?Sized,
impl<T> BorrowMut for T where
T: ?Sized,
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impl<T> BorrowMut for T where
T: ?Sized,
fn borrow_mut(&mut self) -> &mut T
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fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
impl<T, U> TryInto for T where
U: TryFrom<T>,
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impl<T, U> TryInto for T where
U: TryFrom<T>,
type Error = <U as TryFrom<T>>::Error
try_from
)The type returned in the event of a conversion error.
fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
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fn try_into(self) -> Result<U, <U as TryFrom<T>>::Error>
try_from
)Performs the conversion.
impl<T> Any for T where
T: 'static + ?Sized,
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impl<T> Any for T where
T: 'static + ?Sized,
fn get_type_id(&self) -> TypeId
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fn get_type_id(&self) -> TypeId
🔬 This is a nightly-only experimental API. (get_type_id
)
this method will likely be replaced by an associated static
Gets the TypeId
of self
. Read more
impl<T> DeserializeOwned for T where
T: Deserialize<'de>,
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impl<T> DeserializeOwned for T where
T: Deserialize<'de>,
impl<T> Same for T
impl<T> Same for T
type Output = T
Should always be Self
impl<T> Erased for T
impl<T> Erased for T