org.apache.spark.ml.regression

Class AFTSurvivalRegression

java.lang.Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<AFTSurvivalRegressionModel>

org.apache.spark.ml.regression.AFTSurvivalRegression

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable

public class AFTSurvivalRegression
extends Estimator<AFTSurvivalRegressionModel>
implements Logging

:: Experimental :: Fit a parametric survival regression model named accelerated failure time (AFT) model (https://en.wikipedia.org/wiki/Accelerated_failure_time_model) based on the Weibull distribution of the survival time.

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AFTSurvivalRegression()
AFTSurvivalRegression(java.lang.String uid)

Method Summary

Methods

Modifier and Type	Method and Description
Param<java.lang.String>	censorCol() Param for censor column name.
AFTSurvivalRegression	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
protected RDD<org.apache.spark.ml.regression.AFTPoint>	extractAFTPoints(DataFrame dataset) Extract featuresCol, labelCol and censorCol from input dataset, and put it in an RDD with strong types.
AFTSurvivalRegressionModel	fit(DataFrame dataset) Fits a model to the input data.
java.lang.String	getCensorCol()
double[]	getQuantileProbabilities()
java.lang.String	getQuantilesCol()
boolean	hasQuantilesCol() Checks whether the input has quantiles column name.
static AFTSurvivalRegression	load(java.lang.String path)
DoubleArrayParam	quantileProbabilities() Param for quantile probabilities array.
Param<java.lang.String>	quantilesCol() Param for quantiles column name.
AFTSurvivalRegression	setCensorCol(java.lang.String value)
AFTSurvivalRegression	setFeaturesCol(java.lang.String value)
AFTSurvivalRegression	setFitIntercept(boolean value) Set if we should fit the intercept Default is true.
AFTSurvivalRegression	setLabelCol(java.lang.String value)
AFTSurvivalRegression	setMaxIter(int value) Set the maximum number of iterations.
AFTSurvivalRegression	setPredictionCol(java.lang.String value)
AFTSurvivalRegression	setQuantileProbabilities(double[] value)
AFTSurvivalRegression	setQuantilesCol(java.lang.String value)
AFTSurvivalRegression	setTol(double value) Set the convergence tolerance of iterations.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
java.lang.String	uid() An immutable unique ID for the object and its derivatives.
StructType	validateAndTransformSchema(StructType schema, boolean fitting) Validates and transforms the input schema with the provided param map.

Methods inherited from class org.apache.spark.ml.Estimator

fit, fit, fit, fit

Methods inherited from class org.apache.spark.ml.PipelineStage

transformSchema

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn, validateParams

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString

Methods inherited from interface org.apache.spark.Logging

initializeIfNecessary, initializeLogging, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

AFTSurvivalRegression

public AFTSurvivalRegression(java.lang.String uid)

AFTSurvivalRegression

public AFTSurvivalRegression()

Method Detail

load

public static AFTSurvivalRegression load(java.lang.String path)

uid

public java.lang.String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setFeaturesCol

public AFTSurvivalRegression setFeaturesCol(java.lang.String value)

setLabelCol

public AFTSurvivalRegression setLabelCol(java.lang.String value)

setCensorCol

public AFTSurvivalRegression setCensorCol(java.lang.String value)

setPredictionCol

public AFTSurvivalRegression setPredictionCol(java.lang.String value)

setQuantileProbabilities

public AFTSurvivalRegression setQuantileProbabilities(double[] value)

setQuantilesCol

public AFTSurvivalRegression setQuantilesCol(java.lang.String value)

setFitIntercept

public AFTSurvivalRegression setFitIntercept(boolean value)

Set if we should fit the intercept Default is true.

Parameters:

value - (undocumented)

Returns:

(undocumented)

setMaxIter

public AFTSurvivalRegression setMaxIter(int value)

Set the maximum number of iterations. Default is 100.

Parameters:

value - (undocumented)

Returns:

(undocumented)

setTol

public AFTSurvivalRegression 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)

extractAFTPoints

protected RDD<org.apache.spark.ml.regression.AFTPoint> extractAFTPoints(DataFrame dataset)

Extract featuresCol, labelCol and censorCol from input dataset, and put it in an RDD with strong types.

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

fit

public AFTSurvivalRegressionModel fit(DataFrame dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<AFTSurvivalRegressionModel>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Derives the output schema from the input schema.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public AFTSurvivalRegression copy(ParamMap extra)

Description copied from interface: Params

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.

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<AFTSurvivalRegressionModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

See Also:

defaultCopy()

censorCol

public Param<java.lang.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.

Returns:

(undocumented)

getCensorCol

public java.lang.String getCensorCol()

quantileProbabilities

public DoubleArrayParam 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.

Returns:

(undocumented)

getQuantileProbabilities

public double[] getQuantileProbabilities()

quantilesCol

public Param<java.lang.String> quantilesCol()

Param for quantiles column name. This column will output quantiles of corresponding quantileProbabilities if it is set.

Returns:

(undocumented)

getQuantilesCol

public java.lang.String getQuantilesCol()

hasQuantilesCol

public boolean hasQuantilesCol()

Checks whether the input has quantiles column name.

validateAndTransformSchema

public StructType validateAndTransformSchema(StructType schema,
                                    boolean fitting)

Validates and transforms the input schema with the provided param map.

Parameters:

schema - input schema

fitting - whether this is in fitting or prediction

Returns:

output schema