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, labelCol
featuresCol, getFeaturesCol
getPredictionCol, predictionCol
clear, copy, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn
toString, uid
fitIntercept, getFitIntercept
getMaxIter, maxIter
getRegParam, regParam
getWeightCol, weightCol
aggregationDepth, 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_, uninitialize
Param<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)
PredictorParams
validateAndTransformSchema
in interface PredictorParams
schema
- input schemafitting
- whether this is in fittingfeaturesDataType
- SQL DataType for FeaturesType.
E.g., VectorUDT
for vector features.DoubleParam variancePower()