matrix
0.1
API
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matrix/ai.dragonfly.math.matrix.ml.data/StaticSupervisedData

StaticSupervisedData

ai.dragonfly.math.matrix.ml.data.StaticSupervisedData
class StaticSupervisedData[M <: Int, N <: Int](labeledExamples: Array[LabeledVec[N]])(using x$2: ValueOf[M], x$3: ValueOf[N]) extends SupervisedData[M, N]

Attributes

Source:
Data.scala
Graph
Supertypes
trait SupervisedData[M, N]
trait Data[M, N]
class Object
trait Matchable
class Any

Members list

Concise view

Value members

Concrete methods

def domainComponent(i: Int): Interval[Double]

Attributes

Source:
Data.scala
def example(i: Int): Vec[N]

Attributes

Source:
Data.scala
def labeledExample(i: Int): LabeledVec[N]

Attributes

Source:
Data.scala

Inherited methods

def domainBias: Vec[N]

Attributes

Inherited from:
Data
Source:
Data.scala
def rangeBias: Double

Attributes

Inherited from:
SupervisedData
Source:
Data.scala

Concrete fields

override val X: Matrix[M, N]

Attributes

Source:
Data.scala
override val Y: Matrix[M, 1]

Attributes

Source:
Data.scala
val intervals: Array[Interval[Double]]

Attributes

Source:
Data.scala
override val labelStats: EstimatedGaussian

Attributes

Source:
Data.scala
override val sampleMean: Vec[N]

Attributes

Source:
Data.scala
override val sampleStandardDeviation: Vec[N]

Attributes

Source:
Data.scala
override val sampleVariance: Vec[N]

Attributes

Source:
Data.scala
val temp: (EstimatedGaussian, Vec[N], Vec[N], Vec[N], Array[Interval[Double]])

Attributes

Source:
Data.scala
override val y: Vec[M]

Attributes

Source:
Data.scala

Inherited fields

val dimension: Int

Attributes

Inherited from:
Data
Source:
Data.scala
val sampleSize: Int

Attributes

Inherited from:
Data
Source:
Data.scala
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