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. | 
getLabelCol, labelColfeaturesCol, getFeaturesColgetPredictionCol, predictionColclear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, 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()