class
L2R_LrFunction_Binomial extends Function
Instance Constructors
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new
L2R_LrFunction_Binomial(prob: BinomialProblem, Cp: Double, Cn: Double)
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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def
Hv(s: Array[Double], Hs: Array[Double]): Unit
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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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def
fun(w: Array[Double]): Double
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final
def
getClass(): Class[_]
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lazy val
get_nr_variable: Int
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def
grad(w: Array[Double], g: Array[Double]): Unit
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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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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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
Inherited from Function
Inherited from AnyRef
Inherited from Any
Binomial logistic regression function with offsets.
This is horrifically mutable code, but is made to line up with how other liblinear functions were done in Java. Also, did the while-loop thing to iterate over arrays since it is a bit more efficient than equivalent for-loops in Scala.