Spark 3.0.0 ScalaDoc < Back

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package root

Definition Classes
root
package org

Definition Classes
root
package apache

Definition Classes
org
package spark
Core Spark functionality.
Core Spark functionality. org.apache.spark.SparkContext serves as the main entry point to Spark, while org.apache.spark.rdd.RDD is the data type representing a distributed collection, and provides most parallel operations.
In addition, org.apache.spark.rdd.PairRDDFunctions contains operations available only on RDDs of key-value pairs, such as groupByKey and join; org.apache.spark.rdd.DoubleRDDFunctions contains operations available only on RDDs of Doubles; and org.apache.spark.rdd.SequenceFileRDDFunctions contains operations available on RDDs that can be saved as SequenceFiles. These operations are automatically available on any RDD of the right type (e.g. RDD[(Int, Int)] through implicit conversions.
Java programmers should reference the org.apache.spark.api.java package for Spark programming APIs in Java.
Classes and methods marked with Experimental are user-facing features which have not been officially adopted by the Spark project. These are subject to change or removal in minor releases.
Classes and methods marked with Developer API are intended for advanced users want to extend Spark through lower level interfaces. These are subject to changes or removal in minor releases.

Definition Classes
apache
package ml
DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.
DataFrame-based machine learning APIs to let users quickly assemble and configure practical machine learning pipelines.

Definition Classes
spark
package regression

Definition Classes
ml
AFTSurvivalRegression
AFTSurvivalRegressionModel
DecisionTreeRegressionModel
DecisionTreeRegressor
GBTRegressionModel
GBTRegressor
GeneralizedLinearRegression
GeneralizedLinearRegressionModel
GeneralizedLinearRegressionSummary
GeneralizedLinearRegressionTrainingSummary
IsotonicRegression
IsotonicRegressionModel
LinearRegression
LinearRegressionModel
LinearRegressionSummary
LinearRegressionTrainingSummary
RandomForestRegressionModel
RandomForestRegressor
RegressionModel

org.apache.spark.ml.regression

GBTRegressionModel

Companion class GBTRegressionModel

object GBTRegressionModel extends MLReadable[GBTRegressionModel] with Serializable

Annotations: @Since( "2.0.0" )

Linear Supertypes

Serializable, Serializable, MLReadable[GBTRegressionModel], AnyRef, Any

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GBTRegressionModel
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final def ==(arg0: Any): Boolean

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final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

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final def eq(arg0: AnyRef): Boolean

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def equals(arg0: Any): Boolean

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def finalize(): Unit

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@native()
def hashCode(): Int

Definition Classes
AnyRef → Any
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@native()
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def load(path: String): GBTRegressionModel
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
GBTRegressionModel → MLReadable
Annotations
@Since( "2.0.0" )
Note
Implementing classes should override this to be Java-friendly.
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
Annotations
@native()
final def notifyAll(): Unit

Definition Classes
AnyRef
Annotations
@native()
def read: MLReader[GBTRegressionModel]
Returns an MLReader instance for this class.
Returns an MLReader instance for this class.

Definition Classes
GBTRegressionModel → MLReadable
Annotations
@Since( "2.0.0" )
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

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final def wait(): Unit

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@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
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@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
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@native() @throws( ... )

Packages

GBTRegressionModel

Companion class GBTRegressionModel

object GBTRegressionModel extends MLReadable[GBTRegressionModel] with Serializable

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from MLReadable[GBTRegressionModel]

Inherited from AnyRef

Inherited from Any

Members

Packages

GBTRegressionModel 

Companion class GBTRegressionModel

object GBTRegressionModel extends MLReadable[GBTRegressionModel] with Serializable

Value Members

Inherited from Serializable

Inherited from Serializable

Inherited from MLReadable[GBTRegressionModel]

Inherited from AnyRef

Inherited from Any

Members

GBTRegressionModel