選取您的 Cookie 偏好設定

我們使用提供自身網站和服務所需的基本 Cookie 和類似工具。我們使用效能 Cookie 收集匿名統計資料,以便了解客戶如何使用我們的網站並進行改進。基本 Cookie 無法停用,但可以按一下「自訂」或「拒絕」以拒絕效能 Cookie。

如果您同意,AWS 與經核准的第三方也會使用 Cookie 提供實用的網站功能、記住您的偏好設定,並顯示相關內容,包括相關廣告。若要接受或拒絕所有非必要 Cookie,請按一下「接受」或「拒絕」。若要進行更詳細的選擇,請按一下「自訂」。

FindMatchesParameters - AWS Glue
此頁面尚未翻譯為您的語言。 請求翻譯

FindMatchesParameters

The parameters to configure the find matches transform.

Contents

AccuracyCostTradeoff

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.

Type: Double

Valid Range: Minimum value of 0.0. Maximum value of 1.0.

Required: No

EnforceProvidedLabels

The value to switch on or off to force the output to match the provided labels from users. If the value is True, the find matches transform forces the output to match the provided labels. The results override the normal conflation results. If the value is False, the find 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.

Type: Boolean

Required: No

PrecisionRecallTradeoff

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.

Type: Double

Valid Range: Minimum value of 0.0. Maximum value of 1.0.

Required: No

PrimaryKeyColumnName

The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 1024.

Pattern: [\u0020-\uD7FF\uE000-\uFFFD\uD800\uDC00-\uDBFF\uDFFF\t]*

Required: No

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following:

隱私權網站條款Cookie 偏好設定
© 2025, Amazon Web Services, Inc.或其附屬公司。保留所有權利。