org.apache.spark.ml.fpm

Class FPGrowth

Object

org.apache.spark.ml.PipelineStage

org.apache.spark.ml.Estimator<FPGrowthModel>

org.apache.spark.ml.fpm.FPGrowth

All Implemented Interfaces:

java.io.Serializable, Logging, FPGrowthParams, Params, HasPredictionCol, DefaultParamsWritable, Identifiable, MLWritable

public class FPGrowth
extends Estimator<FPGrowthModel>
implements FPGrowthParams, DefaultParamsWritable

:: Experimental :: A parallel FP-growth algorithm to mine frequent itemsets. The algorithm is described in Li et al., PFP: Parallel FP-Growth for Query Recommendation. PFP distributes computation in such a way that each worker executes an independent group of mining tasks. The FP-Growth algorithm is described in Han et al., Mining frequent patterns without candidate generation. Note null values in the itemsCol column are ignored during fit().

See Also:

Association rule learning (Wikipedia), Serialized Form

Constructor Summary

Constructors

Constructor and Description
FPGrowth()
FPGrowth(String uid)

Method Summary

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.
static FPGrowth	load(String path)
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) :: DeveloperApi ::
String	uid() An immutable unique ID for the object and its derivatives.

Methods inherited from class org.apache.spark.ml.Estimator

fit, fit, fit, fit

Methods inherited from class Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface org.apache.spark.ml.fpm.FPGrowthParams

getItemsCol, getMinConfidence, getMinSupport, getNumPartitions, itemsCol, minConfidence, minSupport, numPartitions, validateAndTransformSchema

Methods inherited from interface org.apache.spark.ml.param.shared.HasPredictionCol

getPredictionCol, predictionCol

Methods inherited from interface org.apache.spark.ml.param.Params

clear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

Methods inherited from interface org.apache.spark.ml.util.Identifiable

toString

Methods inherited from interface org.apache.spark.ml.util.DefaultParamsWritable

write

Methods inherited from interface org.apache.spark.ml.util.MLWritable

save

Methods inherited from interface org.apache.spark.internal.Logging

initializeLogging, initializeLogIfNecessary, initializeLogIfNecessary, isTraceEnabled, log_, log, logDebug, logDebug, logError, logError, logInfo, logInfo, logName, logTrace, logTrace, logWarning, logWarning

Constructor Detail

FPGrowth

public FPGrowth(String uid)

FPGrowth

public FPGrowth()

Method Detail

load

public static FPGrowth load(String path)

read

public static MLReader<T> read()

uid

public String uid()

Description copied from interface: Identifiable

An immutable unique ID for the object and its derivatives.

Specified by:

uid in interface Identifiable

Returns:

(undocumented)

setMinSupport

public FPGrowth setMinSupport(double value)

setNumPartitions

public FPGrowth setNumPartitions(int value)

setMinConfidence

public FPGrowth setMinConfidence(double value)

setItemsCol

public FPGrowth setItemsCol(String value)

setPredictionCol

public FPGrowth setPredictionCol(String value)

fit

public FPGrowthModel fit(Dataset<?> dataset)

Description copied from class: Estimator

Fits a model to the input data.

Specified by:

fit in class Estimator<FPGrowthModel>

Parameters:

dataset - (undocumented)

Returns:

(undocumented)

transformSchema

public StructType transformSchema(StructType schema)

Description copied from class: PipelineStage

:: DeveloperApi ::

Check transform validity and derive the output schema from the input schema.

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.

Specified by:

transformSchema in class PipelineStage

Parameters:

schema - (undocumented)

Returns:

(undocumented)

copy

public FPGrowth copy(ParamMap extra)

Description copied from interface: Params

Creates a copy of this instance with the same UID and some extra params. Subclasses should implement this method and set the return type properly. See defaultCopy().

Specified by:

copy in interface Params

Specified by:

copy in class Estimator<FPGrowthModel>

Parameters:

extra - (undocumented)

Returns:

(undocumented)