org.apache.spark.ml.regression

Interface AFTSurvivalRegressionParams

All Superinterfaces:

HasAggregationDepth, HasFeaturesCol, HasFitIntercept, HasLabelCol, HasMaxIter, HasPredictionCol, HasTol, Identifiable, org.apache.spark.internal.Logging, Params, PredictorParams, java.io.Serializable

All Known Implementing Classes:

AFTSurvivalRegression, AFTSurvivalRegressionModel

public interface AFTSurvivalRegressionParams
extends PredictorParams, HasMaxIter, HasTol, HasFitIntercept, HasAggregationDepth, org.apache.spark.internal.Logging

Params for accelerated failure time (AFT) regression.

Method Summary

Modifier and Type	Method and Description
Param<String>	censorCol() Param for censor column name.
String	getCensorCol()
double[]	getQuantileProbabilities()
String	getQuantilesCol()
boolean	hasQuantilesCol() Checks whether the input has quantiles column name.
DoubleArrayParam	quantileProbabilities() Param for quantile probabilities array.
Param<String>	quantilesCol() Param for quantiles column name.
StructType	validateAndTransformSchema(StructType schema, boolean fitting) Validates and transforms the input schema with the provided param map.

Methods inherited from interface org.apache.spark.ml.PredictorParams

extractInstances, extractInstances, validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.param.shared.HasLabelCol

getLabelCol, labelCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasFeaturesCol

featuresCol, getFeaturesCol

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

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

clear, copy, 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, uid

Methods inherited from interface org.apache.spark.ml.param.shared.HasMaxIter

getMaxIter, maxIter

Methods inherited from interface org.apache.spark.ml.param.shared.HasTol

getTol, tol

Methods inherited from interface org.apache.spark.ml.param.shared.HasFitIntercept

fitIntercept, getFitIntercept

Methods inherited from interface org.apache.spark.ml.param.shared.HasAggregationDepth

aggregationDepth, getAggregationDepth

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

Method Detail

censorCol

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

String getCensorCol()

getQuantileProbabilities

double[] getQuantileProbabilities()

getQuantilesCol

String getQuantilesCol()

hasQuantilesCol

boolean hasQuantilesCol()

Checks whether the input has quantiles column name.

quantileProbabilities

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)

quantilesCol

Param<String> quantilesCol()

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

Returns:

(undocumented)

validateAndTransformSchema

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