LinearRegressionSummary

Value Members

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. val explainedVariance: Double

   

   Returns the explained variance regression score.

   Returns the explained variance regression score. explainedVariance = 1 - variance(y - \hat{y}) / variance(y) Reference: http://en.wikipedia.org/wiki/Explained_variation

9. def finalize(): Unit

   

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

    

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11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. val labelCol: String

    

14. val meanAbsoluteError: Double

    

    Returns the mean absolute error, which is a risk function corresponding to the expected value of the absolute error loss or l1-norm loss.

15. val meanSquaredError: Double

    

    Returns the mean squared error, which is a risk function corresponding to the expected value of the squared error loss or quadratic loss.

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

    

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17. final def notify(): Unit

    

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18. final def notifyAll(): Unit

    

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19. val predictionCol: String

    

20. val predictions: DataFrame

    

    predictions outputted by the model's transform method.

21. val r2: Double

    

    Returns R², the coefficient of determination.

    Returns R², the coefficient of determination. Reference: http://en.wikipedia.org/wiki/Coefficient_of_determination

22. lazy val residuals: DataFrame

    

    Residuals (label - predicted value)

23. val rootMeanSquaredError: Double

    

    Returns the root mean squared error, which is defined as the square root of the mean squared error.

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

    

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25. def toString(): String

    

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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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