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The AWS SDK for Kotlin client for Glue
// Code generated by smithy-kotlin-codegen. DO NOT EDIT!
package aws.sdk.kotlin.services.glue.model
import aws.smithy.kotlin.runtime.SdkDsl
/**
* The parameters to configure the find matches transform.
*/
public class FindMatchesParameters private constructor(builder: Builder) {
/**
* 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.
*/
public val accuracyCostTradeoff: kotlin.Double? = builder.accuracyCostTradeoff
/**
* 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.
*/
public val enforceProvidedLabels: kotlin.Boolean? = builder.enforceProvidedLabels
/**
* 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.
*/
public val precisionRecallTradeoff: kotlin.Double? = builder.precisionRecallTradeoff
/**
* The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
*/
public val primaryKeyColumnName: kotlin.String? = builder.primaryKeyColumnName
public companion object {
public operator fun invoke(block: Builder.() -> kotlin.Unit): aws.sdk.kotlin.services.glue.model.FindMatchesParameters = Builder().apply(block).build()
}
override fun toString(): kotlin.String = buildString {
append("FindMatchesParameters(")
append("accuracyCostTradeoff=$accuracyCostTradeoff,")
append("enforceProvidedLabels=$enforceProvidedLabels,")
append("precisionRecallTradeoff=$precisionRecallTradeoff,")
append("primaryKeyColumnName=$primaryKeyColumnName")
append(")")
}
override fun hashCode(): kotlin.Int {
var result = accuracyCostTradeoff?.hashCode() ?: 0
result = 31 * result + (enforceProvidedLabels?.hashCode() ?: 0)
result = 31 * result + (precisionRecallTradeoff?.hashCode() ?: 0)
result = 31 * result + (primaryKeyColumnName?.hashCode() ?: 0)
return result
}
override fun equals(other: kotlin.Any?): kotlin.Boolean {
if (this === other) return true
if (other == null || this::class != other::class) return false
other as FindMatchesParameters
if (!(accuracyCostTradeoff?.equals(other.accuracyCostTradeoff) ?: (other.accuracyCostTradeoff == null))) return false
if (enforceProvidedLabels != other.enforceProvidedLabels) return false
if (!(precisionRecallTradeoff?.equals(other.precisionRecallTradeoff) ?: (other.precisionRecallTradeoff == null))) return false
if (primaryKeyColumnName != other.primaryKeyColumnName) return false
return true
}
public inline fun copy(block: Builder.() -> kotlin.Unit = {}): aws.sdk.kotlin.services.glue.model.FindMatchesParameters = Builder(this).apply(block).build()
@SdkDsl
public class Builder {
/**
* 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.
*/
public var accuracyCostTradeoff: kotlin.Double? = null
/**
* 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.
*/
public var enforceProvidedLabels: kotlin.Boolean? = null
/**
* 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.
*/
public var precisionRecallTradeoff: kotlin.Double? = null
/**
* The name of a column that uniquely identifies rows in the source table. Used to help identify matching records.
*/
public var primaryKeyColumnName: kotlin.String? = null
@PublishedApi
internal constructor()
@PublishedApi
internal constructor(x: aws.sdk.kotlin.services.glue.model.FindMatchesParameters) : this() {
this.accuracyCostTradeoff = x.accuracyCostTradeoff
this.enforceProvidedLabels = x.enforceProvidedLabels
this.precisionRecallTradeoff = x.precisionRecallTradeoff
this.primaryKeyColumnName = x.primaryKeyColumnName
}
@PublishedApi
internal fun build(): aws.sdk.kotlin.services.glue.model.FindMatchesParameters = FindMatchesParameters(this)
internal fun correctErrors(): Builder {
return this
}
}
}