[−][src]Struct rusoto_glue::FindMatchesMetrics
The evaluation metrics for the find matches algorithm. The quality of your machine learning transform is measured by getting your transform to predict some matches and comparing the results to known matches from the same dataset. The quality metrics are based on a subset of your data, so they are not precise.
Fields
area_under_pr_curve: Option<f64>
The area under the precision/recall curve (AUPRC) is a single number measuring the overall quality of the transform, that is independent of the choice made for precision vs. recall. Higher values indicate that you have a more attractive precision vs. recall tradeoff.
For more information, see Precision and recall in Wikipedia.
confusion_matrix: Option<ConfusionMatrix>
The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.
For more information, see Confusion matrix in Wikipedia.
f1: Option<f64>
The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.
For more information, see F1 score in Wikipedia.
precision: Option<f64>
The precision metric indicates when often your transform is correct when it predicts a match. Specifically, it measures how well the transform finds true positives from the total true positives possible.
For more information, see Precision and recall in Wikipedia.
recall: Option<f64>
The recall metric indicates that for an actual match, how often your transform predicts the match. Specifically, it measures how well the transform finds true positives from the total records in the source data.
For more information, see Precision and recall in Wikipedia.
Trait Implementations
impl Clone for FindMatchesMetrics
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pub fn clone(&self) -> FindMatchesMetrics
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pub fn clone_from(&mut self, source: &Self)
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impl Debug for FindMatchesMetrics
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impl Default for FindMatchesMetrics
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pub fn default() -> FindMatchesMetrics
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impl<'de> Deserialize<'de> for FindMatchesMetrics
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pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
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__D: Deserializer<'de>,
impl PartialEq<FindMatchesMetrics> for FindMatchesMetrics
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pub fn eq(&self, other: &FindMatchesMetrics) -> bool
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pub fn ne(&self, other: &FindMatchesMetrics) -> bool
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impl StructuralPartialEq for FindMatchesMetrics
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Auto Trait Implementations
impl RefUnwindSafe for FindMatchesMetrics
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impl Send for FindMatchesMetrics
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impl Sync for FindMatchesMetrics
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impl Unpin for FindMatchesMetrics
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impl UnwindSafe for FindMatchesMetrics
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Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
pub fn borrow_mut(&mut self) -> &mut T
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impl<T> DeserializeOwned for T where
T: for<'de> Deserialize<'de>,
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T: for<'de> Deserialize<'de>,
impl<T> From<T> for T
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T> Instrument for T
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pub fn instrument(self, span: Span) -> Instrumented<Self>
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pub fn in_current_span(self) -> Instrumented<Self>
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> Same<T> for T
type Output = T
Should always be Self
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
type Owned = T
The resulting type after obtaining ownership.
pub fn to_owned(&self) -> T
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pub fn clone_into(&self, target: &mut T)
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impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
type Error = Infallible
The type returned in the event of a conversion error.
pub fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,