public interface IsotonicRegressionBase extends Params, HasFeaturesCol, HasLabelCol, HasPredictionCol, HasWeightCol, Logging
Modifier and Type | Method and Description |
---|---|
RDD<scala.Tuple3<Object,Object,Object>> |
extractWeightedLabeledPoints(Dataset<?> dataset)
Extracts (label, feature, weight) from input dataset.
|
IntParam |
featureIndex()
Param for the index of the feature if
featuresCol is a vector column (default: 0 ), no
effect otherwise. |
int |
getFeatureIndex() |
boolean |
getIsotonic() |
boolean |
hasWeightCol()
Checks whether the input has weight column.
|
BooleanParam |
isotonic()
Param for whether the output sequence should be isotonic/increasing (true) or
antitonic/decreasing (false).
|
StructType |
validateAndTransformSchema(StructType schema,
boolean fitting)
Validates and transforms input schema.
|
featuresCol, getFeaturesCol
getLabelCol, labelCol
getPredictionCol, predictionCol
getWeightCol, weightCol
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
toString, uid
initializeForcefully, initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning
RDD<scala.Tuple3<Object,Object,Object>> extractWeightedLabeledPoints(Dataset<?> dataset)
dataset
- (undocumented)IntParam featureIndex()
featuresCol
is a vector column (default: 0
), no
effect otherwise.int getFeatureIndex()
boolean getIsotonic()
boolean hasWeightCol()
BooleanParam isotonic()
StructType validateAndTransformSchema(StructType schema, boolean fitting)
schema
- input schemafitting
- whether this is in fitting or prediction