AUC

Compute the "Area Under the Curve" for a collection of predictions. Uses the Trapezoid method to compute the area.

Internally a linspace is defined using the given number of samples. Each point in the linspace represents a threshold which is used to build a confusion matrix. The area is then defined on this list of confusion matrices.

AUCMetric which is given to the aggregate selects the function to apply on the confusion matrix prior to the AUC calculation.

metric: Which function to apply on the confusion matrix.
samples: Number of samples to use for the curve definition.

Linear Supertypes

Serializable, Product, Equals, Aggregator[Prediction[Boolean, Double], MetricCurve, Double], Serializable, AnyRef, Any

Instance Constructors

new AUC(metric: AUCMetric, samples: Int = 100)

metric
Which function to apply on the confusion matrix.
samples
Number of samples to use for the curve definition.

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
def andThenPresent[D](present2: (Double) ⇒ D): Aggregator[Prediction[Boolean, Double], MetricCurve, D]

Definition Classes
Aggregator
def append(l: MetricCurve, r: Prediction[Boolean, Double]): MetricCurve

Definition Classes
Aggregator
def appendAll(old: MetricCurve, items: TraversableOnce[Prediction[Boolean, Double]]): MetricCurve

Definition Classes
Aggregator
def apply(inputs: TraversableOnce[Prediction[Boolean, Double]]): Double

Definition Classes
Aggregator
def applyCumulatively[In <: TraversableOnce[Prediction[Boolean, Double]], Out](inputs: In)(implicit bf: CanBuildFrom[In, Double, Out]): Out

Definition Classes
Aggregator
def applyOption(inputs: TraversableOnce[Prediction[Boolean, Double]]): Option[Double]

Definition Classes
Aggregator
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def composePrepare[A1](prepare2: (A1) ⇒ Prediction[Boolean, Double]): Aggregator[A1, MetricCurve, Double]

Definition Classes
Aggregator
def cumulativeIterator(inputs: Iterator[Prediction[Boolean, Double]]): Iterator[Double]

Definition Classes
Aggregator
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
def join[A2 <: Prediction[Boolean, Double], B2, C2](that: Aggregator[A2, B2, C2]): Aggregator[A2, (MetricCurve, B2), (Double, C2)]

Definition Classes
Aggregator
def lift: MonoidAggregator[Prediction[Boolean, Double], Option[MetricCurve], Option[Double]]

Definition Classes
Aggregator
val metric: AUCMetric

Which function to apply on the confusion matrix.
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def prepare(input: Prediction[Boolean, Double]): MetricCurve

Definition Classes
AUC → Aggregator
def present(c: MetricCurve): Double

Definition Classes
AUC → Aggregator
def reduce(items: TraversableOnce[MetricCurve]): MetricCurve

Definition Classes
Aggregator
def reduce(l: MetricCurve, r: MetricCurve): MetricCurve

Definition Classes
Aggregator
def reduceOption(items: TraversableOnce[MetricCurve]): Option[MetricCurve]

Definition Classes
Aggregator
val samples: Int

Number of samples to use for the curve definition.
def semigroup: Semigroup[MetricCurve]

Definition Classes
AUC → Aggregator
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toFold: Fold[Prediction[Boolean, Double], Option[Double]]

Definition Classes
Aggregator
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( ... )
def zip[A2, B2, C2](ag2: Aggregator[A2, B2, C2]): Aggregator[(Prediction[Boolean, Double], A2), (MetricCurve, B2), (Double, C2)]

Definition Classes
Aggregator

Related Doc: package noether

case class AUC(metric: AUCMetric, samples: Int = 100) extends Aggregator[Prediction[Boolean, Double], MetricCurve, Double] with Product with Serializable

Instance Constructors

new AUC(metric: AUCMetric, samples: Int = 100)

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def andThenPresent[D](present2: (Double) ⇒ D): Aggregator[Prediction[Boolean, Double], MetricCurve, D]

def append(l: MetricCurve, r: Prediction[Boolean, Double]): MetricCurve

def appendAll(old: MetricCurve, items: TraversableOnce[Prediction[Boolean, Double]]): MetricCurve

def apply(inputs: TraversableOnce[Prediction[Boolean, Double]]): Double

def applyCumulatively[In <: TraversableOnce[Prediction[Boolean, Double]], Out](inputs: In)(implicit bf: CanBuildFrom[In, Double, Out]): Out

def applyOption(inputs: TraversableOnce[Prediction[Boolean, Double]]): Option[Double]

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def composePrepare[A1](prepare2: (A1) ⇒ Prediction[Boolean, Double]): Aggregator[A1, MetricCurve, Double]

def cumulativeIterator(inputs: Iterator[Prediction[Boolean, Double]]): Iterator[Double]

final def eq(arg0: AnyRef): Boolean

def finalize(): Unit

final def getClass(): Class[_]

final def isInstanceOf[T0]: Boolean

def join[A2 <: Prediction[Boolean, Double], B2, C2](that: Aggregator[A2, B2, C2]): Aggregator[A2, (MetricCurve, B2), (Double, C2)]

def lift: MonoidAggregator[Prediction[Boolean, Double], Option[MetricCurve], Option[Double]]

val metric: AUCMetric

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def prepare(input: Prediction[Boolean, Double]): MetricCurve

def present(c: MetricCurve): Double

def reduce(items: TraversableOnce[MetricCurve]): MetricCurve

def reduce(l: MetricCurve, r: MetricCurve): MetricCurve

def reduceOption(items: TraversableOnce[MetricCurve]): Option[MetricCurve]

val samples: Int

def semigroup: Semigroup[MetricCurve]

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

def toFold: Fold[Prediction[Boolean, Double], Option[Double]]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

def zip[A2, B2, C2](ag2: Aggregator[A2, B2, C2]): Aggregator[(Prediction[Boolean, Double], A2), (MetricCurve, B2), (Double, C2)]

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Aggregator[Prediction[Boolean, Double], MetricCurve, Double]

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped