public class AFTSurvivalRegression extends Regressor<Vector,AFTSurvivalRegression,AFTSurvivalRegressionModel> implements AFTSurvivalRegressionParams, DefaultParamsWritable, org.apache.spark.internal.Logging
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.
| Constructor and Description |
|---|
AFTSurvivalRegression() |
AFTSurvivalRegression(String uid) |
| Modifier and Type | Method and Description |
|---|---|
IntParam |
aggregationDepth()
Param for suggested depth for treeAggregate (>= 2).
|
Param<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.
|
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<String> |
quantilesCol()
Param for quantiles column name.
|
static MLReader<T> |
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.
|
featuresCol, fit, labelCol, predictionCol, setFeaturesCol, setLabelCol, setPredictionColparamsequals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitgetCensorCol, getQuantileProbabilities, getQuantilesCol, hasQuantilesCol, validateAndTransformSchemaextractInstances, extractInstances, validateAndTransformSchemagetLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoStringgetMaxItergetFitInterceptgetAggregationDepthgetMaxBlockSizeInMB$init$, 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_, uninitializewritesavepublic AFTSurvivalRegression(String uid)
public AFTSurvivalRegression()
public static AFTSurvivalRegression load(String path)
public static MLReader<T> read()
public final Param<String> censorCol()
AFTSurvivalRegressionParamscensorCol in interface AFTSurvivalRegressionParamspublic final DoubleArrayParam quantileProbabilities()
AFTSurvivalRegressionParamsquantileProbabilities in interface AFTSurvivalRegressionParamspublic final Param<String> quantilesCol()
AFTSurvivalRegressionParamsquantilesCol in interface AFTSurvivalRegressionParamspublic final DoubleParam maxBlockSizeInMB()
HasMaxBlockSizeInMBmaxBlockSizeInMB in interface HasMaxBlockSizeInMBpublic final IntParam aggregationDepth()
HasAggregationDepthaggregationDepth in interface HasAggregationDepthpublic final BooleanParam fitIntercept()
HasFitInterceptfitIntercept in interface HasFitInterceptpublic final DoubleParam tol()
HasTolpublic final IntParam maxIter()
HasMaxItermaxIter in interface HasMaxIterpublic String uid()
Identifiableuid in interface Identifiablepublic AFTSurvivalRegression setCensorCol(String value)
public AFTSurvivalRegression setQuantileProbabilities(double[] value)
public AFTSurvivalRegression setQuantilesCol(String value)
public AFTSurvivalRegression setFitIntercept(boolean value)
value - (undocumented)public AFTSurvivalRegression setMaxIter(int value)
value - (undocumented)public AFTSurvivalRegression setTol(double value)
value - (undocumented)public AFTSurvivalRegression setAggregationDepth(int value)
value - (undocumented)public AFTSurvivalRegression setMaxBlockSizeInMB(double value)
maxBlockSizeInMB.
Default is 0.0, then 1.0 MB will be chosen.
value - (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
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.
transformSchema in class Predictor<Vector,AFTSurvivalRegression,AFTSurvivalRegressionModel>schema - (undocumented)public AFTSurvivalRegression copy(ParamMap extra)
ParamsdefaultCopy().copy in interface Paramscopy in class Predictor<Vector,AFTSurvivalRegression,AFTSurvivalRegressionModel>extra - (undocumented)