org.apache.spark.ml.regression

Class AFTSurvivalRegressionModel

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Transformer

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

org.apache.spark.ml.regression.AFTSurvivalRegressionModel

All Implemented Interfaces:

java.io.Serializable, Logging, Params, Identifiable, MLWritable

public class AFTSurvivalRegressionModel
extends Model<AFTSurvivalRegressionModel>
implements MLWritable

:: Experimental :: Model produced by AFTSurvivalRegression.

See Also:

Serialized Form

Method Summary

Modifier and Type	Method and Description
static IntParam	aggregationDepth()
static Param<String>	censorCol()
Param<String>	censorCol() Param for censor column name.
static Params	clear(Param<?> param)
Vector	coefficients()
AFTSurvivalRegressionModel	copy(ParamMap extra) Creates a copy of this instance with the same UID and some extra params.
static String	explainParam(Param<?> param)
static String	explainParams()
static ParamMap	extractParamMap()
static ParamMap	extractParamMap(ParamMap extra)
static Param<String>	featuresCol()
static BooleanParam	fitIntercept()
static <T> scala.Option<T>	get(Param<T> param)
static int	getAggregationDepth()
static String	getCensorCol()
String	getCensorCol()
static <T> scala.Option<T>	getDefault(Param<T> param)
static String	getFeaturesCol()
static boolean	getFitIntercept()
static String	getLabelCol()
static int	getMaxIter()
static <T> T	getOrDefault(Param<T> param)
static Param<Object>	getParam(String paramName)
static String	getPredictionCol()
static double[]	getQuantileProbabilities()
double[]	getQuantileProbabilities()
static String	getQuantilesCol()
String	getQuantilesCol()
static double	getTol()
static <T> boolean	hasDefault(Param<T> param)
static boolean	hasParam(String paramName)
static boolean	hasParent()
boolean	hasQuantilesCol() Checks whether the input has quantiles column name.
double	intercept()
static boolean	isDefined(Param<?> param)
static boolean	isSet(Param<?> param)
static Param<String>	labelCol()
static AFTSurvivalRegressionModel	load(String path)
static IntParam	maxIter()
static Param<?>[]	params()
static void	parent_$eq(Estimator<M> x$1)
static Estimator<M>	parent()
double	predict(Vector features)
static Param<String>	predictionCol()
Vector	predictQuantiles(Vector features)
static DoubleArrayParam	quantileProbabilities()
DoubleArrayParam	quantileProbabilities() Param for quantile probabilities array.
static Param<String>	quantilesCol()
Param<String>	quantilesCol() Param for quantiles column name.
static MLReader<AFTSurvivalRegressionModel>	read()
static void	save(String path)
double	scale()
static <T> Params	set(Param<T> param, T value)
AFTSurvivalRegressionModel	setFeaturesCol(String value)
static M	setParent(Estimator<M> parent)
AFTSurvivalRegressionModel	setPredictionCol(String value)
AFTSurvivalRegressionModel	setQuantileProbabilities(double[] value)
AFTSurvivalRegressionModel	setQuantilesCol(String value)
static DoubleParam	tol()
static String	toString()
Dataset<Row>	transform(Dataset<?> dataset) Transforms the input dataset.
StructType	transformSchema(StructType schema) :: DeveloperApi ::
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.
MLWriter	write() Returns an MLWriter instance for this ML instance.

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

hasParent, parent, setParent

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

transform, transform, transform

Methods inherited from class Object

equals, 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

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

toString

Methods inherited from interface org.apache.spark.internal.Logging

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

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

save

Method Detail

read

public static MLReader<AFTSurvivalRegressionModel> read()

load

public static AFTSurvivalRegressionModel load(String path)

toString

public static String toString()

params

public static Param<?>[] params()

explainParam

public static String explainParam(Param<?> param)

explainParams

public static String explainParams()

isSet

public static final boolean isSet(Param<?> param)

isDefined

public static final boolean isDefined(Param<?> param)

hasParam

public static boolean hasParam(String paramName)

getParam

public static Param<Object> getParam(String paramName)

set

public static final <T> Params set(Param<T> param,
                                   T value)

get

public static final <T> scala.Option<T> get(Param<T> param)

clear

public static final Params clear(Param<?> param)

getOrDefault

public static final <T> T getOrDefault(Param<T> param)

getDefault

public static final <T> scala.Option<T> getDefault(Param<T> param)

hasDefault

public static final <T> boolean hasDefault(Param<T> param)

extractParamMap

public static final ParamMap extractParamMap(ParamMap extra)

extractParamMap

public static final ParamMap extractParamMap()

parent

public static Estimator<M> parent()

parent_$eq

public static void parent_$eq(Estimator<M> x$1)

setParent

public static M setParent(Estimator<M> parent)

hasParent

public static boolean hasParent()

featuresCol

public static final Param<String> featuresCol()

getFeaturesCol

public static final String getFeaturesCol()

labelCol

public static final Param<String> labelCol()

getLabelCol

public static final String getLabelCol()

predictionCol

public static final Param<String> predictionCol()

getPredictionCol

public static final String getPredictionCol()

maxIter

public static final IntParam maxIter()

getMaxIter

public static final int getMaxIter()

tol

public static final DoubleParam tol()

getTol

public static final double getTol()

fitIntercept

public static final BooleanParam fitIntercept()

getFitIntercept

public static final boolean getFitIntercept()

aggregationDepth

public static final IntParam aggregationDepth()

getAggregationDepth

public static final int getAggregationDepth()

censorCol

public static final Param<String> censorCol()

getCensorCol

public static String getCensorCol()

quantileProbabilities

public static final DoubleArrayParam quantileProbabilities()

getQuantileProbabilities

public static double[] getQuantileProbabilities()

quantilesCol

public static final Param<String> quantilesCol()

getQuantilesCol

public static String getQuantilesCol()

save

public static void save(String path)
                 throws java.io.IOException

Throws:

java.io.IOException

uid

public 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)

coefficients

public Vector coefficients()

intercept

public double intercept()

scale

public double scale()

setFeaturesCol

public AFTSurvivalRegressionModel setFeaturesCol(String value)

setPredictionCol

public AFTSurvivalRegressionModel setPredictionCol(String value)

setQuantileProbabilities

public AFTSurvivalRegressionModel setQuantileProbabilities(double[] value)

setQuantilesCol

public AFTSurvivalRegressionModel setQuantilesCol(String value)

predictQuantiles

public Vector predictQuantiles(Vector features)

predict

public double predict(Vector features)

transform

public Dataset<Row> transform(Dataset<?> dataset)

Description copied from class: Transformer

Transforms the input dataset.

Specified by:

transform in class Transformer

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

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.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public AFTSurvivalRegressionModel 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. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Model<AFTSurvivalRegressionModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)

write

public MLWriter write()

Description copied from interface: MLWritable

Returns an MLWriter instance for this ML instance.

Specified by:

write in interface MLWritable

Returns:

(undocumented)

censorCol

public 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.

Returns:

(undocumented)

getCensorCol

public 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<String> quantilesCol()

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

Returns:

(undocumented)

getQuantilesCol

public 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