glue/aws.sdk.kotlin.services.glue.model/FindMatchesMetrics

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.

Types

Builder

class Builder

Companion

object Companion

Properties

areaUnderPrCurve

val areaUnderPrCurve: Double?

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.

columnImportances

val columnImportances: List<ColumnImportance>?

A list of ColumnImportance structures containing column importance metrics, sorted in order of descending importance.

confusionMatrix

val confusionMatrix: ConfusionMatrix?

The confusion matrix shows you what your transform is predicting accurately and what types of errors it is making.

val f1: Double?

The maximum F1 metric indicates the transform's accuracy between 0 and 1, where 1 is the best accuracy.

precision

val precision: Double?

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.

recall

val recall: Double?

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.

Functions

copy

inline fun copy(block: FindMatchesMetrics.Builder.() -> Unit = {}): FindMatchesMetrics

equals

open operator override fun equals(other: Any?): Boolean

hashCode

open override fun hashCode(): Int

toString

open override fun toString(): String