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object LinearRegression extends DefaultParamsReadable[LinearRegression] with Serializable

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@Since( "1.6.0" )
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  1. LinearRegression
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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. val MAX_FEATURES_FOR_NORMAL_SOLVER: Int

    When using LinearRegression.solver == "normal", the solver must limit the number of features to at most this number.

    When using LinearRegression.solver == "normal", the solver must limit the number of features to at most this number. The entire covariance matrix XTX will be collected to the driver. This limit helps prevent memory overflow errors.

    Annotations
    @Since( "2.1.0" )
  5. final def asInstanceOf[T0]: T0
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  6. def clone(): AnyRef
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    protected[lang]
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    @throws( ... ) @native()
  7. final def eq(arg0: AnyRef): Boolean
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  8. def equals(arg0: Any): Boolean
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  9. def finalize(): Unit
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    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]
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    @native()
  11. def hashCode(): Int
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    @native()
  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
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  13. def load(path: String): LinearRegression

    Reads an ML instance from the input path, a shortcut of read.load(path).

    Reads an ML instance from the input path, a shortcut of read.load(path).

    Definition Classes
    LinearRegressionMLReadable
    Annotations
    @Since( "1.6.0" )
    Note

    Implementing classes should override this to be Java-friendly.

  14. final def ne(arg0: AnyRef): Boolean
    Definition Classes
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  15. final def notify(): Unit
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    @native()
  16. final def notifyAll(): Unit
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    @native()
  17. def read: MLReader[LinearRegression]

    Returns an MLReader instance for this class.

    Returns an MLReader instance for this class.

    Definition Classes
    DefaultParamsReadableMLReadable
  18. final def synchronized[T0](arg0: ⇒ T0): T0
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  19. def toString(): String
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  20. final def wait(): Unit
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    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit
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    @throws( ... )
  22. final def wait(arg0: Long): Unit
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    @throws( ... ) @native()

Inherited from Serializable

Inherited from Serializable

Inherited from MLReadable[LinearRegression]

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