object LinearRegression extends DefaultParamsReadable[LinearRegression] with Serializable
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final
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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" )
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final
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isInstanceOf[T0]: Boolean
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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
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- @Since( "1.6.0" )
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Implementing classes should override this to be Java-friendly.
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notifyAll(): Unit
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def
read: MLReader[LinearRegression]
Returns an
MLReader
instance for this class.Returns an
MLReader
instance for this class.- Definition Classes
- DefaultParamsReadable → MLReadable
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synchronized[T0](arg0: ⇒ T0): T0
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