#[non_exhaustive]pub struct PerformanceMetrics {
pub properties: Option<HashMap<String, String>>,
}
Expand description
Measurements of how well the MLModel
performed on known observations. One of the following metrics is returned, based on the type of the MLModel
:
-
BinaryAUC: The binary
MLModel
uses the Area Under the Curve (AUC) technique to measure performance. -
RegressionRMSE: The 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: The multiclass
MLModel
uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
Fields (Non-exhaustive)§
This struct is marked as non-exhaustive
Struct { .. }
syntax; cannot be matched against without a wildcard ..
; and struct update syntax will not work.properties: Option<HashMap<String, String>>
Implementations§
Source§impl PerformanceMetrics
impl PerformanceMetrics
Sourcepub fn builder() -> PerformanceMetricsBuilder
pub fn builder() -> PerformanceMetricsBuilder
Creates a new builder-style object to manufacture PerformanceMetrics
.
Trait Implementations§
Source§impl Clone for PerformanceMetrics
impl Clone for PerformanceMetrics
Source§fn clone(&self) -> PerformanceMetrics
fn clone(&self) -> PerformanceMetrics
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Debug for PerformanceMetrics
impl Debug for PerformanceMetrics
Source§impl PartialEq for PerformanceMetrics
impl PartialEq for PerformanceMetrics
impl StructuralPartialEq for PerformanceMetrics
Auto Trait Implementations§
impl Freeze for PerformanceMetrics
impl RefUnwindSafe for PerformanceMetrics
impl Send for PerformanceMetrics
impl Sync for PerformanceMetrics
impl Unpin for PerformanceMetrics
impl UnwindSafe for PerformanceMetrics
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