Instance Constructors
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new
PerLabelInfoGain(labels: Iterable[L], labelToFeatures: (L) ⇒ F)
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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def
init(labels: Iterable[L]): Unit
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final
def
isInstanceOf[T0]: Boolean
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var
labelEntropies: Array[Double]
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
top(labelValue: DiscreteValue, n: Int): TopN[String]
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def
top(labelIndex: Int, n: Int): TopN[String]
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Calculate the information gain between the binary variable "in class" / "not in class" and the binary variable "has feature" / "does not have feature" for every (label,feature) combination.
0.10