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Trainer

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object Trainer extends Serializable

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. final def eq(arg0: AnyRef): Boolean

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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  9. final def getClass(): Class[_]

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  10. def hashCode(): Int

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  11. final def isInstanceOf[T0]: Boolean

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  12. final def ne(arg0: AnyRef): Boolean

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  13. def newL1LogLossMIRATrainer[T, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], summer: ExpectationInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), average: Boolean = true, addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  14. def newL1LogLossTrainer[T, Y, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], summer: ExpectationInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  15. def newL1MIRATrainer[T, Y, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], argmaxer: LossAugmentedArgmaxInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), average: Boolean = true, addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  16. def newL1MarginRankTrainer[T, W, MaxerS](argmaxer: LossAugmentedArgmaxInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, MaxerS, MaxerS], C: Double = 1.0, gamma: Double = 0.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, MaxerS, MaxerS]

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  17. def newL1MaxMarginTrainer[T, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], argmaxer: LossAugmentedArgmaxInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS] = NullIterationCallback(), C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  18. def newL2MaxMarginTrainer[T, Y, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], argmaxer: LossAugmentedArgmaxInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), addInitialConstraint: Option[W] = None)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  19. def newPerceptronTrainer[T, Y, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], argmaxer: ArgmaxInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], learningRate: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), average: Boolean = true)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  20. def newStochasticGradientDescentTrainer[T, W, OracleS, MaxerS](oracleInferencer: OracleInferencer[T, W, OracleS], summer: ExpectationInferencer[T, W, MaxerS], iterationCallback: IterationCallback[T, W, OracleS, MaxerS], C: Double = 1.0, learningRate: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts(), average: Boolean = true)(implicit space: MutableInnerProductModule[W, Double]): Trainer[T, W, OracleS, MaxerS]

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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  23. final def synchronized[T0](arg0: ⇒ T0): T0

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  24. def toString(): String

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  25. def trainL1MaxMarginMulticlassClassifier[L, F, W](labels: IndexedSeq[L], data: Seq[LabeledDatum[L, F]], labelConjoiner: (L, F) ⇒ W, initialConstraint: W, iterationCallback: IterationCallback[LabeledDatum[L, F], W, Unit, Unit] = ..., oneSlackFormulation: Boolean = true, C: Double = 1.0, maxNumIters: Int = 100, opts: LogoOpts = new LogoOpts())(implicit space: MutableInnerProductModule[W, Double]): MulticlassClassifier[L, F, W]

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  26. final def wait(): Unit

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  27. final def wait(arg0: Long, arg1: Int): Unit

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  28. final def wait(arg0: Long): Unit

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