Interface CfnMLTransform.FindMatchesParametersProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnMLTransform.FindMatchesParametersProperty.Jsii$Proxy
- Enclosing class:
CfnMLTransform
Example:
// The code below shows an example of how to instantiate this type. // The values are placeholders you should change. import software.amazon.awscdk.services.glue.*; FindMatchesParametersProperty findMatchesParametersProperty = FindMatchesParametersProperty.builder() .primaryKeyColumnName("primaryKeyColumnName") // the properties below are optional .accuracyCostTradeoff(123) .enforceProvidedLabels(false) .precisionRecallTradeoff(123) .build();
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Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic final class
A builder forCfnMLTransform.FindMatchesParametersProperty
static final class
An implementation forCfnMLTransform.FindMatchesParametersProperty
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Method Summary
Modifier and TypeMethodDescriptionbuilder()
default Number
The value that is selected when tuning your transform for a balance between accuracy and cost.default Object
The value to switch on or off to force the output to match the provided labels from users.default Number
The value selected when tuning your transform for a balance between precision and recall.The name of a column that uniquely identifies rows in the source table.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getPrimaryKeyColumnName
The name of a column that uniquely identifies rows in the source table.Used to help identify matching records.
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getAccuracyCostTradeoff
The value that is selected when tuning your transform for a balance between accuracy and cost.A value of 0.5 means that the system balances accuracy and cost concerns. A value of 1.0 means a bias purely for accuracy, which typically results in a higher cost, sometimes substantially higher. A value of 0.0 means a bias purely for cost, which results in a less accurate
FindMatches
transform, sometimes with unacceptable accuracy.Accuracy measures how well the transform finds true positives and true negatives. Increasing accuracy requires more machine resources and cost. But it also results in increased recall.
Cost measures how many compute resources, and thus money, are consumed to run the transform.
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getEnforceProvidedLabels
The value to switch on or off to force the output to match the provided labels from users.If the value is
True
, thefind matches
transform forces the output to match the provided labels. The results override the normal conflation results. If the value isFalse
, thefind matches
transform does not ensure all the labels provided are respected, and the results rely on the trained model.Note that setting this value to true may increase the conflation execution time.
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getPrecisionRecallTradeoff
The value selected when tuning your transform for a balance between precision and recall.A value of 0.5 means no preference; a value of 1.0 means a bias purely for precision, and a value of 0.0 means a bias for recall. Because this is a tradeoff, choosing values close to 1.0 means very low recall, and choosing values close to 0.0 results in very low precision.
The precision metric indicates how often your model is correct when it predicts a match.
The recall metric indicates that for an actual match, how often your model predicts the match.
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builder
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