Instance Constructors
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new
HashFeatureVectorVariable(initVals: Iterable[Any])
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new
HashFeatureVectorVariable()
Concrete Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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def
!==(other: Var): Boolean
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final
def
##(): Int
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def
++=(cs: Iterable[Any]): Unit
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def
+=(c: Any): Unit
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def
+=(c: Any, incr: Double): Unit
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final
def
:=(newValue: Value): Unit
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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def
===(other: Var): Boolean
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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def
contains(index: Int): Boolean
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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
increment(incr: Tensor)(implicit d: DiffList): Unit
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def
increment(index: Int, incr: Double)(implicit d: DiffList): Unit
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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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def
printName: String
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def
set(newValue: Value)(implicit d: DiffList): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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def
update(index: Int, newValue: Double)(implicit d: DiffList): Unit
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final
def
value: Value
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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
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def
zero(implicit d: DiffList): Unit
A variable whose value is a SparseTensor1 whose length matches the size of a DiscreteDomain, and whose dimensions each correspond to the result of running a hash function on elements added to the vector using +=. These can be used as feature vectors where one wants to avoid a large or growing CategoricalDomain. The 'dimensionDomain' is abstract.