class StochasticAveragedGradient[T] extends FirstOrderMinimizer[T, BatchDiffFunction[T]]
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Type Members
- case class History(stepSize: Double, range: IndexedSeq[Int], currentSum: T, previousGradients: IndexedSeq[T], nextPos: Int) extends Product with Serializable
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type
State = FirstOrderMinimizer.State[T, Info, History]
- Definition Classes
- FirstOrderMinimizer
Value Members
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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def
adjust(newX: T, newGrad: T, newVal: Double): (Double, T)
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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def
adjustFunction(f: BatchDiffFunction[T]): BatchDiffFunction[T]
- Attributes
- protected
- Definition Classes
- FirstOrderMinimizer
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final
def
asInstanceOf[T0]: T0
- Definition Classes
- Any
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def
calculateObjective(f: BatchDiffFunction[T], x: T, history: History): (Double, T)
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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def
chooseDescentDirection(state: State, f: BatchDiffFunction[T]): T
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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def
clone(): AnyRef
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- protected[java.lang]
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- @native() @HotSpotIntrinsicCandidate() @throws( ... )
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val
convergenceCheck: ConvergenceCheck[T]
- Definition Classes
- FirstOrderMinimizer
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def
determineStepSize(state: State, f: BatchDiffFunction[T], direction: T): Double
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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final
def
getClass(): Class[_]
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- @native() @HotSpotIntrinsicCandidate()
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def
hashCode(): Int
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def
infiniteIterations(f: BatchDiffFunction[T], state: State): Iterator[State]
- Definition Classes
- FirstOrderMinimizer
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def
initialHistory(f: BatchDiffFunction[T], init: T): History
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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def
initialState(f: BatchDiffFunction[T], init: T): State
- Attributes
- protected
- Definition Classes
- FirstOrderMinimizer
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
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def
iterations(f: BatchDiffFunction[T], init: T): Iterator[State]
- Definition Classes
- FirstOrderMinimizer
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def
logger: LazyLogger
- Attributes
- protected
- Definition Classes
- SerializableLogging
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def
minimize(f: BatchDiffFunction[T], init: T): T
- Definition Classes
- FirstOrderMinimizer → Minimizer
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def
minimizeAndReturnState(f: BatchDiffFunction[T], init: T): State
- Definition Classes
- FirstOrderMinimizer
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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
- Definition Classes
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def
takeStep(state: State, dir: T, stepSize: Double): T
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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def
toString(): String
- Definition Classes
- AnyRef → Any
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def
updateHistory(newX: T, newGrad: T, newVal: Double, f: BatchDiffFunction[T], oldState: State): History
- Attributes
- protected
- Definition Classes
- StochasticAveragedGradient → FirstOrderMinimizer
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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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final
def
wait(): Unit
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- @throws( ... )