public interface GeneralizedLinearRegressionBase extends PredictorParams, HasFitIntercept, HasMaxIter, HasTol, HasRegParam, HasWeightCol, HasSolver, HasAggregationDepth, org.apache.spark.internal.Logging
| Modifier and Type | Method and Description |
|---|---|
Param<String> |
family()
Param for the name of family which is a description of the error distribution
to be used in the model.
|
String |
getFamily() |
String |
getLink() |
double |
getLinkPower() |
String |
getLinkPredictionCol() |
String |
getOffsetCol() |
double |
getVariancePower() |
boolean |
hasLinkPredictionCol()
Checks whether we should output link prediction.
|
boolean |
hasOffsetCol()
Checks whether offset column is set and nonempty.
|
boolean |
hasWeightCol()
Checks whether weight column is set and nonempty.
|
Param<String> |
link()
Param for the name of link function which provides the relationship
between the linear predictor and the mean of the distribution function.
|
DoubleParam |
linkPower()
Param for the index in the power link function.
|
Param<String> |
linkPredictionCol()
Param for link prediction (linear predictor) column name.
|
Param<String> |
offsetCol()
Param for offset column name.
|
Param<String> |
solver()
The solver algorithm for optimization.
|
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting,
DataType featuresDataType)
Validates and transforms the input schema with the provided param map.
|
DoubleParam |
variancePower()
Param for the power in the variance function of the Tweedie distribution which provides
the relationship between the variance and mean of the distribution.
|
extractInstances, extractInstancesgetLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwntoString, uidfitIntercept, getFitInterceptgetMaxIter, maxItergetRegParam, regParamgetWeightCol, weightColaggregationDepth, getAggregationDepth$init$, 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_, uninitializeParam<String> family()
String getFamily()
String getLink()
double getLinkPower()
String getLinkPredictionCol()
String getOffsetCol()
double getVariancePower()
boolean hasLinkPredictionCol()
boolean hasOffsetCol()
boolean hasWeightCol()
Param<String> link()
linkPower.
DoubleParam linkPower()
variancePower, which matches the R "statmod"
package.
Param<String> linkPredictionCol()
Param<String> offsetCol()
Param<String> solver()
StructType validateAndTransformSchema(StructType schema, boolean fitting, DataType featuresDataType)
PredictorParamsvalidateAndTransformSchema in interface PredictorParamsschema - input schemafitting - whether this is in fittingfeaturesDataType - SQL DataType for FeaturesType.
E.g., VectorUDT for vector features.DoubleParam variancePower()