Packages

object LinearRegression extends DefaultParamsReadable[LinearRegression] with Serializable

Annotations
@Since( "1.6.0" )
Source
LinearRegression.scala
Linear Supertypes
Serializable, Serializable, DefaultParamsReadable[LinearRegression], MLReadable[LinearRegression], AnyRef, Any
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Inherited
  1. LinearRegression
  2. Serializable
  3. Serializable
  4. DefaultParamsReadable
  5. MLReadable
  6. AnyRef
  7. Any
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Visibility
  1. Public
  2. All

Value Members

  1. 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" )
  2. 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
    LinearRegression → MLReadable
    Annotations
    @Since( "1.6.0" )
    Note

    Implementing classes should override this to be Java-friendly.

  3. def read: MLReader[LinearRegression]

    Returns an MLReader instance for this class.

    Returns an MLReader instance for this class.

    Definition Classes
    DefaultParamsReadable → MLReadable