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// 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
        }
    }
}




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