BinaryClassificationMetrics

Metrics for binary classification models

Precision: Overall precision of model, TP / (TP + FP)
Recall: Overall recall of model, TP / (TP + FN)
F1: Overall F1 score of model, 2 / (1 / Precision + 1 / Recall)
AuROC: AuROC of model
AuPR: AuPR of model
Error: Error of model
TP: True positive count at Spark's default decision threshold (0.5)
TN: True negative count at Spark's default decision threshold (0.5)
FP: False positive count at Spark's default decision threshold (0.5)
FN: False negative count at Spark's default decision threshold (0.5)
ThresholdMetrics: Metrics across different threshold values

Linear Supertypes

Product, Equals, EvaluationMetrics, JsonLike, Serializable, Serializable, AnyRef, Any

Instance Constructors

new BinaryClassificationMetrics(Precision: Double, Recall: Double, F1: Double, AuROC: Double, AuPR: Double, Error: Double, TP: Double, TN: Double, FP: Double, FN: Double, ThresholdMetrics: BinaryThresholdMetrics)

Precision

Overall precision of model, TP / (TP + FP)

Recall

Overall recall of model, TP / (TP + FN)

F1

Overall F1 score of model, 2 / (1 / Precision + 1 / Recall)

AuROC

AuROC of model

AuPR

AuPR of model

Error

Error of model

TP

True positive count at Spark's default decision threshold (0.5)

TN

True negative count at Spark's default decision threshold (0.5)

FP

False positive count at Spark's default decision threshold (0.5)

FN

False negative count at Spark's default decision threshold (0.5)

ThresholdMetrics

Metrics across different threshold values

Value Members

final def !=(arg0: Any): Boolean

Definition Classes

AnyRef → Any
final def ##(): Int

Definition Classes

AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes

AnyRef → Any
val AuPR: Double

AuPR of model
val AuROC: Double

AuROC of model
val Error: Double

Error of model
val F1: Double

Overall F1 score of model, 2 / (1 / Precision + 1 / Recall)
val FN: Double

False negative count at Spark's default decision threshold (0.5)
val FP: Double

False positive count at Spark's default decision threshold (0.5)
val Precision: Double

Overall precision of model, TP / (TP + FP)
val Recall: Double

Overall recall of model, TP / (TP + FN)
val TN: Double

True negative count at Spark's default decision threshold (0.5)
val TP: Double

True positive count at Spark's default decision threshold (0.5)
val ThresholdMetrics: BinaryThresholdMetrics

Metrics across different threshold values
final def asInstanceOf[T0]: T0

Definition Classes

Any
def clone(): AnyRef

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( ... )
final def eq(arg0: AnyRef): Boolean

Definition Classes

AnyRef
def finalize(): Unit

Attributes

protected[java.lang]

Definition Classes

AnyRef

Annotations

@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes

AnyRef → Any
final def isInstanceOf[T0]: Boolean

Definition Classes

Any
final def ne(arg0: AnyRef): Boolean

Definition Classes

AnyRef
final def notify(): Unit

Definition Classes

AnyRef
final def notifyAll(): Unit

Definition Classes

AnyRef
def prCurve: Seq[(Double, Double)]
def rocCurve: Seq[(Double, Double)]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes

AnyRef
def toJson(pretty: Boolean = true): String

Write this instance to json string

Write this instance to json string

pretty

should pretty print

returns

json string of the instance

Definition Classes

JsonLike
def toMap: Map[String, Any]

Convert metrics class to a map

Convert metrics class to a map

returns

a map from metric name to metric value

Definition Classes

EvaluationMetrics
def toMetadata(skipUnsupported: Boolean = false): Metadata

Convert metrics into Metadata for saving

Convert metrics into Metadata for saving

skipUnsupported

skip unsupported values

returns

Metadata metadata

Definition Classes

EvaluationMetrics

Exceptions thrown

RuntimeException in case of unsupported value type
def toString(): String

This instance json string

This instance json string

returns

json string of the instance

Definition Classes

JsonLike → AnyRef → Any
final def wait(): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes

AnyRef

Annotations

@throws( ... )

Related Doc: package evaluators

case class BinaryClassificationMetrics(Precision: Double, Recall: Double, F1: Double, AuROC: Double, AuPR: Double, Error: Double, TP: Double, TN: Double, FP: Double, FN: Double, ThresholdMetrics: BinaryThresholdMetrics) extends EvaluationMetrics with Product with Serializable

Instance Constructors

new BinaryClassificationMetrics(Precision: Double, Recall: Double, F1: Double, AuROC: Double, AuPR: Double, Error: Double, TP: Double, TN: Double, FP: Double, FN: Double, ThresholdMetrics: BinaryThresholdMetrics)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

val AuPR: Double

val AuROC: Double

val Error: Double

val F1: Double

val FN: Double

val FP: Double

val Precision: Double

val Recall: Double

val TN: Double

val TP: Double

val ThresholdMetrics: BinaryThresholdMetrics

final def asInstanceOf[T0]: T0

def clone(): AnyRef

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def prCurve: Seq[(Double, Double)]

def rocCurve: Seq[(Double, Double)]

final def synchronized[T0](arg0: ⇒ T0): T0

def toJson(pretty: Boolean = true): String

def toMap: Map[String, Any]

def toMetadata(skipUnsupported: Boolean = false): Metadata

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit

Inherited from Product

Inherited from Equals

Inherited from EvaluationMetrics

Inherited from JsonLike

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped