AFTSurvivalRegression (Spark 3.5.5 JavaDoc) (original) (raw)

Object
- org.apache.spark.ml.PipelineStage
- - org.apache.spark.ml.Estimator
    - - org.apache.spark.ml.Predictor<FeaturesType,Learner,M>
        * * org.apache.spark.ml.regression.Regressor<Vector,AFTSurvivalRegression,AFTSurvivalRegressionModel>
        * * org.apache.spark.ml.regression.AFTSurvivalRegression
All Implemented Interfaces:
java.io.Serializable, org.apache.spark.internal.Logging, Params, HasAggregationDepth, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasMaxBlockSizeInMB, HasMaxIter, HasPredictionCol, HasTol, PredictorParams, AFTSurvivalRegressionParams, DefaultParamsWritable, Identifiable, MLWritable

public class AFTSurvivalRegression
extends Regressor<Vector,AFTSurvivalRegression,AFTSurvivalRegressionModel>
implements AFTSurvivalRegressionParams, DefaultParamsWritable, org.apache.spark.internal.Logging
Fit a parametric survival regression model named accelerated failure time (AFT) model (see Accelerated failure time model (Wikipedia)) based on the Weibull distribution of the survival time.
Since 3.1.0, it supports stacking instances into blocks and using GEMV for better performance. The block size will be 1.0 MB, if param maxBlockSizeInMB is set 0.0 by default.
See Also:
Serialized Form

Nested Class Summary

 * ### Nested classes/interfaces inherited from interface org.apache.spark.internal.Logging  
 `org.apache.spark.internal.Logging.SparkShellLoggingFilter`

Constructor Summary

Constructors

Constructor and Description
AFTSurvivalRegression()
AFTSurvivalRegression(String uid)

Method Summary

All Methods Static Methods Instance Methods Concrete Methods

Modifier and Type	Method and Description
IntParam	aggregationDepth() Param for suggested depth for treeAggregate (>= 2).
Param	censorCol() Param for censor column name.
AFTSurvivalRegression	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
BooleanParam	fitIntercept() Param for whether to fit an intercept term.
static AFTSurvivalRegression	load(String path)
DoubleParam	maxBlockSizeInMB() Param for Maximum memory in MB for stacking input data into blocks.
IntParam	maxIter() Param for maximum number of iterations (>= 0).
DoubleArrayParam	quantileProbabilities() Param for quantile probabilities array.
Param	quantilesCol() Param for quantiles column name.
static MLReader	read()
AFTSurvivalRegression	setAggregationDepth(int value) Suggested depth for treeAggregate (greater than or equal to 2).
AFTSurvivalRegression	setCensorCol(String value)
AFTSurvivalRegression	setFitIntercept(boolean value) Set if we should fit the intercept Default is true.
AFTSurvivalRegression	setMaxBlockSizeInMB(double value) Sets the value of param maxBlockSizeInMB.
AFTSurvivalRegression	setMaxIter(int value) Set the maximum number of iterations.
AFTSurvivalRegression	setQuantileProbabilities(double[] value)
AFTSurvivalRegression	setQuantilesCol(String value)
AFTSurvivalRegression	setTol(double value) Set the convergence tolerance of iterations.
DoubleParam	tol() Param for the convergence tolerance for iterative algorithms (>= 0).
StructType	transformSchema(StructType schema) Check transform validity and derive the output schema from the input schema.
String	uid() An immutable unique ID for the object and its derivatives.

   * ### Methods inherited from class org.apache.spark.ml.[Predictor](../../../../../org/apache/spark/ml/Predictor.html "class in org.apache.spark.ml")  
   `[featuresCol](../../../../../org/apache/spark/ml/Predictor.html#featuresCol--), [fit](../../../../../org/apache/spark/ml/Predictor.html#fit-org.apache.spark.sql.Dataset-), [labelCol](../../../../../org/apache/spark/ml/Predictor.html#labelCol--), [predictionCol](../../../../../org/apache/spark/ml/Predictor.html#predictionCol--), [setFeaturesCol](../../../../../org/apache/spark/ml/Predictor.html#setFeaturesCol-java.lang.String-), [setLabelCol](../../../../../org/apache/spark/ml/Predictor.html#setLabelCol-java.lang.String-), [setPredictionCol](../../../../../org/apache/spark/ml/Predictor.html#setPredictionCol-java.lang.String-)`  
   * ### Methods inherited from class org.apache.spark.ml.[Estimator](../../../../../org/apache/spark/ml/Estimator.html "class in org.apache.spark.ml")  
   `[fit](../../../../../org/apache/spark/ml/Estimator.html#fit-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamMap-), [fit](../../../../../org/apache/spark/ml/Estimator.html#fit-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-org.apache.spark.ml.param.ParamPair...-), [fit](../../../../../org/apache/spark/ml/Estimator.html#fit-org.apache.spark.sql.Dataset-org.apache.spark.ml.param.ParamPair-scala.collection.Seq-), [fit](../../../../../org/apache/spark/ml/Estimator.html#fit-org.apache.spark.sql.Dataset-scala.collection.Seq-)`  
   * ### Methods inherited from class org.apache.spark.ml.[PipelineStage](../../../../../org/apache/spark/ml/PipelineStage.html "class in org.apache.spark.ml")  
   `[params](../../../../../org/apache/spark/ml/PipelineStage.html#params--)`  
   * ### Methods inherited from class Object  
   `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`  
   * ### Methods inherited from interface org.apache.spark.ml.regression.[AFTSurvivalRegressionParams](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html "interface in org.apache.spark.ml.regression")  
   `[getCensorCol](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#getCensorCol--), [getQuantileProbabilities](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#getQuantileProbabilities--), [getQuantilesCol](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#getQuantilesCol--), [hasQuantilesCol](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#hasQuantilesCol--), [validateAndTransformSchema](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-)`  
   * ### Methods inherited from interface org.apache.spark.ml.[PredictorParams](../../../../../org/apache/spark/ml/PredictorParams.html "interface in org.apache.spark.ml")  
   `[validateAndTransformSchema](../../../../../org/apache/spark/ml/PredictorParams.html#validateAndTransformSchema-org.apache.spark.sql.types.StructType-boolean-org.apache.spark.sql.types.DataType-)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasLabelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getLabelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html#getLabelCol--), [labelCol](../../../../../org/apache/spark/ml/param/shared/HasLabelCol.html#labelCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html "interface in org.apache.spark.ml.param.shared")  
   `[featuresCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#featuresCol--), [getFeaturesCol](../../../../../org/apache/spark/ml/param/shared/HasFeaturesCol.html#getFeaturesCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html "interface in org.apache.spark.ml.param.shared")  
   `[getPredictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#getPredictionCol--), [predictionCol](../../../../../org/apache/spark/ml/param/shared/HasPredictionCol.html#predictionCol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")  
   `[clear](../../../../../org/apache/spark/ml/param/Params.html#clear-org.apache.spark.ml.param.Param-), [copyValues](../../../../../org/apache/spark/ml/param/Params.html#copyValues-T-org.apache.spark.ml.param.ParamMap-), [defaultCopy](../../../../../org/apache/spark/ml/param/Params.html#defaultCopy-org.apache.spark.ml.param.ParamMap-), [defaultParamMap](../../../../../org/apache/spark/ml/param/Params.html#defaultParamMap--), [explainParam](../../../../../org/apache/spark/ml/param/Params.html#explainParam-org.apache.spark.ml.param.Param-), [explainParams](../../../../../org/apache/spark/ml/param/Params.html#explainParams--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap--), [extractParamMap](../../../../../org/apache/spark/ml/param/Params.html#extractParamMap-org.apache.spark.ml.param.ParamMap-), [get](../../../../../org/apache/spark/ml/param/Params.html#get-org.apache.spark.ml.param.Param-), [getDefault](../../../../../org/apache/spark/ml/param/Params.html#getDefault-org.apache.spark.ml.param.Param-), [getOrDefault](../../../../../org/apache/spark/ml/param/Params.html#getOrDefault-org.apache.spark.ml.param.Param-), [getParam](../../../../../org/apache/spark/ml/param/Params.html#getParam-java.lang.String-), [hasDefault](../../../../../org/apache/spark/ml/param/Params.html#hasDefault-org.apache.spark.ml.param.Param-), [hasParam](../../../../../org/apache/spark/ml/param/Params.html#hasParam-java.lang.String-), [isDefined](../../../../../org/apache/spark/ml/param/Params.html#isDefined-org.apache.spark.ml.param.Param-), [isSet](../../../../../org/apache/spark/ml/param/Params.html#isSet-org.apache.spark.ml.param.Param-), [onParamChange](../../../../../org/apache/spark/ml/param/Params.html#onParamChange-org.apache.spark.ml.param.Param-), [paramMap](../../../../../org/apache/spark/ml/param/Params.html#paramMap--), [params](../../../../../org/apache/spark/ml/param/Params.html#params--), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.Param-T-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-org.apache.spark.ml.param.ParamPair-), [set](../../../../../org/apache/spark/ml/param/Params.html#set-java.lang.String-java.lang.Object-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-org.apache.spark.ml.param.Param-T-), [setDefault](../../../../../org/apache/spark/ml/param/Params.html#setDefault-scala.collection.Seq-), [shouldOwn](../../../../../org/apache/spark/ml/param/Params.html#shouldOwn-org.apache.spark.ml.param.Param-)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")  
   `[toString](../../../../../org/apache/spark/ml/util/Identifiable.html#toString--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#getMaxIter--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")  
   `[getTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#getTol--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html "interface in org.apache.spark.ml.param.shared")  
   `[getFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html#getFitIntercept--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html "interface in org.apache.spark.ml.param.shared")  
   `[getAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html#getAggregationDepth--)`  
   * ### Methods inherited from interface org.apache.spark.ml.param.shared.[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")  
   `[getMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#getMaxBlockSizeInMB--)`  
   * ### Methods inherited from interface org.apache.spark.internal.Logging  
   `$init$, initializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, initLock, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning, org$apache$spark$internal$Logging$$log__$eq, org$apache$spark$internal$Logging$$log_, uninitialize`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[DefaultParamsWritable](../../../../../org/apache/spark/ml/util/DefaultParamsWritable.html "interface in org.apache.spark.ml.util")  
   `[write](../../../../../org/apache/spark/ml/util/DefaultParamsWritable.html#write--)`  
   * ### Methods inherited from interface org.apache.spark.ml.util.[MLWritable](../../../../../org/apache/spark/ml/util/MLWritable.html "interface in org.apache.spark.ml.util")  
   `[save](../../../../../org/apache/spark/ml/util/MLWritable.html#save-java.lang.String-)`

Constructor Detail

 * #### AFTSurvivalRegression  
 public AFTSurvivalRegression(String uid)  
 * #### AFTSurvivalRegression  
 public AFTSurvivalRegression()

Method Detail

* #### load  
public static [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") load(String path)  
* #### read  
public static [MLReader](../../../../../org/apache/spark/ml/util/MLReader.html "class in org.apache.spark.ml.util")<T> read()  
* #### censorCol  
public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> censorCol()  
Param for censor column name. The value of this column could be 0 or 1\. If the value is 1, it means the event has occurred i.e. uncensored; otherwise censored.  
Specified by:  
`[censorCol](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#censorCol--)` in interface `[AFTSurvivalRegressionParams](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html "interface in org.apache.spark.ml.regression")`  
Returns:  
(undocumented)  
* #### quantileProbabilities  
public final [DoubleArrayParam](../../../../../org/apache/spark/ml/param/DoubleArrayParam.html "class in org.apache.spark.ml.param") quantileProbabilities()  
Param for quantile probabilities array. Values of the quantile probabilities array should be in the range (0, 1) and the array should be non-empty.  
Specified by:  
`[quantileProbabilities](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#quantileProbabilities--)` in interface `[AFTSurvivalRegressionParams](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html "interface in org.apache.spark.ml.regression")`  
Returns:  
(undocumented)  
* #### quantilesCol  
public final [Param](../../../../../org/apache/spark/ml/param/Param.html "class in org.apache.spark.ml.param")<String> quantilesCol()  
Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.  
Specified by:  
`[quantilesCol](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html#quantilesCol--)` in interface `[AFTSurvivalRegressionParams](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionParams.html "interface in org.apache.spark.ml.regression")`  
Returns:  
(undocumented)  
* #### maxBlockSizeInMB  
public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") maxBlockSizeInMB()  
Param for Maximum memory in MB for stacking input data into blocks. Data is stacked within partitions. If more than remaining data size in a partition then it is adjusted to the data size. Default 0.0 represents choosing optimal value, depends on specific algorithm. Must be &gt;= 0..  
Specified by:  
`[maxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html#maxBlockSizeInMB--)` in interface `[HasMaxBlockSizeInMB](../../../../../org/apache/spark/ml/param/shared/HasMaxBlockSizeInMB.html "interface in org.apache.spark.ml.param.shared")`  
Returns:  
(undocumented)  
* #### aggregationDepth  
public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") aggregationDepth()  
Param for suggested depth for treeAggregate (&gt;= 2).  
Specified by:  
`[aggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html#aggregationDepth--)` in interface `[HasAggregationDepth](../../../../../org/apache/spark/ml/param/shared/HasAggregationDepth.html "interface in org.apache.spark.ml.param.shared")`  
Returns:  
(undocumented)  
* #### fitIntercept  
public final [BooleanParam](../../../../../org/apache/spark/ml/param/BooleanParam.html "class in org.apache.spark.ml.param") fitIntercept()  
Param for whether to fit an intercept term.  
Specified by:  
`[fitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html#fitIntercept--)` in interface `[HasFitIntercept](../../../../../org/apache/spark/ml/param/shared/HasFitIntercept.html "interface in org.apache.spark.ml.param.shared")`  
Returns:  
(undocumented)  
* #### tol  
public final [DoubleParam](../../../../../org/apache/spark/ml/param/DoubleParam.html "class in org.apache.spark.ml.param") tol()  
Description copied from interface: `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)`  
Param for the convergence tolerance for iterative algorithms (&gt;= 0).  
Specified by:  
`[tol](../../../../../org/apache/spark/ml/param/shared/HasTol.html#tol--)` in interface `[HasTol](../../../../../org/apache/spark/ml/param/shared/HasTol.html "interface in org.apache.spark.ml.param.shared")`  
Returns:  
(undocumented)  
* #### maxIter  
public final [IntParam](../../../../../org/apache/spark/ml/param/IntParam.html "class in org.apache.spark.ml.param") maxIter()  
Description copied from interface: `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)`  
Param for maximum number of iterations (&gt;= 0).  
Specified by:  
`[maxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html#maxIter--)` in interface `[HasMaxIter](../../../../../org/apache/spark/ml/param/shared/HasMaxIter.html "interface in org.apache.spark.ml.param.shared")`  
Returns:  
(undocumented)  
* #### uid  
public String uid()  
An immutable unique ID for the object and its derivatives.  
Specified by:  
`[uid](../../../../../org/apache/spark/ml/util/Identifiable.html#uid--)` in interface `[Identifiable](../../../../../org/apache/spark/ml/util/Identifiable.html "interface in org.apache.spark.ml.util")`  
Returns:  
(undocumented)  
* #### setCensorCol  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setCensorCol(String value)  
* #### setQuantileProbabilities  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setQuantileProbabilities(double[] value)  
* #### setQuantilesCol  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setQuantilesCol(String value)  
* #### setFitIntercept  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setFitIntercept(boolean value)  
Set if we should fit the intercept Default is true.  
Parameters:  
`value` \- (undocumented)  
Returns:  
(undocumented)  
* #### setMaxIter  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setMaxIter(int value)  
Set the maximum number of iterations. Default is 100.  
Parameters:  
`value` \- (undocumented)  
Returns:  
(undocumented)  
* #### setTol  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setTol(double value)  
Set the convergence tolerance of iterations. Smaller value will lead to higher accuracy with the cost of more iterations. Default is 1E-6.  
Parameters:  
`value` \- (undocumented)  
Returns:  
(undocumented)  
* #### setAggregationDepth  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setAggregationDepth(int value)  
Suggested depth for treeAggregate (greater than or equal to 2). If the dimensions of features or the number of partitions are large, this param could be adjusted to a larger size. Default is 2.  
Parameters:  
`value` \- (undocumented)  
Returns:  
(undocumented)  
* #### setMaxBlockSizeInMB  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") setMaxBlockSizeInMB(double value)  
Sets the value of param `maxBlockSizeInMB`. Default is 0.0, then 1.0 MB will be chosen.  
Parameters:  
`value` \- (undocumented)  
Returns:  
(undocumented)  
* #### transformSchema  
public [StructType](../../../../../org/apache/spark/sql/types/StructType.html "class in org.apache.spark.sql.types") transformSchema([StructType](../../../../../org/apache/spark/sql/types/StructType.html "class in org.apache.spark.sql.types") schema)  
Check transform validity and derive the output schema from the input schema.  
 We check validity for interactions between parameters during `transformSchema` and raise an exception if any parameter value is invalid. Parameter value checks which do not depend on other parameters are handled by `Param.validate()`.  
 Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.  
Overrides:  
`[transformSchema](../../../../../org/apache/spark/ml/Predictor.html#transformSchema-org.apache.spark.sql.types.StructType-)` in class `[Predictor](../../../../../org/apache/spark/ml/Predictor.html "class in org.apache.spark.ml")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression"),[AFTSurvivalRegressionModel](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionModel.html "class in org.apache.spark.ml.regression")>`  
Parameters:  
`schema` \- (undocumented)  
Returns:  
(undocumented)  
* #### copy  
public [AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression") copy([ParamMap](../../../../../org/apache/spark/ml/param/ParamMap.html "class in org.apache.spark.ml.param") extra)  
Description copied from interface: `[Params](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)`  
Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See `defaultCopy()`.  
Specified by:  
`[copy](../../../../../org/apache/spark/ml/param/Params.html#copy-org.apache.spark.ml.param.ParamMap-)` in interface `[Params](../../../../../org/apache/spark/ml/param/Params.html "interface in org.apache.spark.ml.param")`  
Specified by:  
`[copy](../../../../../org/apache/spark/ml/Predictor.html#copy-org.apache.spark.ml.param.ParamMap-)` in class `[Predictor](../../../../../org/apache/spark/ml/Predictor.html "class in org.apache.spark.ml")<[Vector](../../../../../org/apache/spark/ml/linalg/Vector.html "interface in org.apache.spark.ml.linalg"),[AFTSurvivalRegression](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegression.html "class in org.apache.spark.ml.regression"),[AFTSurvivalRegressionModel](../../../../../org/apache/spark/ml/regression/AFTSurvivalRegressionModel.html "class in org.apache.spark.ml.regression")>`  
Parameters:  
`extra` \- (undocumented)  
Returns:  
(undocumented)

AFTSurvivalRegression (Spark 3.5.5 JavaDoc) (original) (raw)

Nested Class Summary

Constructor Summary

Method Summary

Constructor Detail

Method Detail