public class FPGrowth extends Estimator<FPGrowthModel> implements FPGrowthParams, DefaultParamsWritable
Modifier and Type | Method and Description |
---|---|
FPGrowth |
copy(ParamMap extra)
Creates a copy of this instance with the same UID and some extra params.
|
FPGrowthModel |
fit(Dataset<?> dataset)
Fits a model to the input data.
|
Param<String> |
itemsCol()
Items column name.
|
static FPGrowth |
load(String path) |
DoubleParam |
minConfidence()
Minimal confidence for generating Association Rule.
|
DoubleParam |
minSupport()
Minimal support level of the frequent pattern.
|
IntParam |
numPartitions()
Number of partitions (at least 1) used by parallel FP-growth.
|
Param<String> |
predictionCol()
Param for prediction column name.
|
static MLReader<T> |
read() |
FPGrowth |
setItemsCol(String value) |
FPGrowth |
setMinConfidence(double value) |
FPGrowth |
setMinSupport(double value) |
FPGrowth |
setNumPartitions(int value) |
FPGrowth |
setPredictionCol(String value) |
StructType |
transformSchema(StructType schema)
Check transform validity and derive the output schema from the input schema.
|
String |
uid()
An immutable unique ID for the object and its derivatives.
|
params
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
getItemsCol, getMinConfidence, getMinSupport, getNumPartitions, validateAndTransformSchema
getPredictionCol
clear, 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
write
save
$init$, 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
public static FPGrowth load(String path)
public static MLReader<T> read()
public Param<String> itemsCol()
FPGrowthParams
itemsCol
in interface FPGrowthParams
public DoubleParam minSupport()
FPGrowthParams
minSupport
in interface FPGrowthParams
public IntParam numPartitions()
FPGrowthParams
numPartitions
in interface FPGrowthParams
public DoubleParam minConfidence()
FPGrowthParams
minConfidence
in interface FPGrowthParams
public final Param<String> predictionCol()
HasPredictionCol
predictionCol
in interface HasPredictionCol
public String uid()
Identifiable
uid
in interface Identifiable
public FPGrowth setMinSupport(double value)
public FPGrowth setNumPartitions(int value)
public FPGrowth setMinConfidence(double value)
public FPGrowth setItemsCol(String value)
public FPGrowth setPredictionCol(String value)
public FPGrowthModel fit(Dataset<?> dataset)
Estimator
fit
in class Estimator<FPGrowthModel>
dataset
- (undocumented)public StructType transformSchema(StructType schema)
PipelineStage
We check validity for interactions between parameters during transformSchema
and
raise an exception if any parameter value is invalid. Parameter value checks which
do not depend on other parameters are handled by Param.validate()
.
Typical implementation should first conduct verification on schema change and parameter validity, including complex parameter interaction checks.
transformSchema
in class PipelineStage
schema
- (undocumented)public FPGrowth copy(ParamMap extra)
Params
defaultCopy()
.copy
in interface Params
copy
in class Estimator<FPGrowthModel>
extra
- (undocumented)