# MultivariateModel

#### trait MultivariateModel extends model.Parameters with OptimizablePredictor[la.Tensor1, la.Tensor1]

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1. MultivariateModel
2. OptimizablePredictor
3. Predictor
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### Concrete Value Members

1. #### final def !=(arg0: AnyRef): Boolean

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2. #### final def !=(arg0: Any): Boolean

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3. #### final def ##(): Int

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4. #### final def ==(arg0: AnyRef): Boolean

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6. #### def Weights(t4: ⇒ Tensor4): Weights4

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7. #### def Weights(t3: ⇒ Tensor3): Weights3

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8. #### def Weights(t2: ⇒ Tensor2): Weights2

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9. #### def Weights(t1: ⇒ Tensor1): Weights1

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10. #### def accumulateObjectiveGradient(accumulator: WeightsMapAccumulator, features: la.Tensor1, gradient: la.Tensor1, weight: Double): Unit

Put gradient of objective with respect to parameters into the accumulator.

Put gradient of objective with respect to parameters into the accumulator. The contract states we cannot mutate the "input" argument inside this method.

accumulator

weight

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MultivariateModelOptimizablePredictor
11. #### final def asInstanceOf[T0]: T0

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12. #### def clone(): AnyRef

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15. #### def finalize(): Unit

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19. #### final def ne(arg0: AnyRef): Boolean

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20. #### final def notify(): Unit

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21. #### final def notifyAll(): Unit

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22. #### val parameters: WeightsSet

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23. #### def predict(feats: la.Tensor1): la.Tensor1

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MultivariateModelPredictor
24. #### final def synchronized[T0](arg0: ⇒ T0): T0

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25. #### def toString(): String

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