class Perceptron extends Serializable
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Instance Constructors
- new Perceptron(nClasses: Int)
Type Members
- type ClassToWeightLearner = Map[ClassNum, WeightLearner]
- type ClassVector = Vector[Score]
- type TimeStamp = Int
- case class WeightLearner(current: Int, total: Int, ts: TimeStamp) extends Product with Serializable
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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final
def
asInstanceOf[T0]: T0
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- def average(w: WeightLearner): Float
-
def
clone(): AnyRef
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- protected[lang]
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- @throws( ... ) @native()
- def current(w: WeightLearner): Float
-
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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- @native()
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
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- val learning: Map[String, Map[String, ClassToWeightLearner]]
- def load(lines: Iterator[String]): Unit
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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- @native()
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final
def
notifyAll(): Unit
- Definition Classes
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- @native()
- def predict(classnumVector: ClassVector): ClassNum
- def score(features: Map[Feature, Score], scoreMethod: (WeightLearner) ⇒ Float): ClassVector
- var seen: TimeStamp
-
final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
- Definition Classes
- Perceptron → AnyRef → Any
- def update(truth: ClassNum, guess: ClassNum, features: Iterable[Feature]): Unit
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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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