FPGrowth (Spark 2.3.0 JavaDoc)

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, Params, DefaultParamsWritable, Identifiable, MLWritable
```
public class FPGrowth
extends Estimator<FPGrowthModel>
implements DefaultParamsWritable
```
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)

Constructors
Constructor and Description
`FPGrowth()`
`FPGrowth(String uid)`

Method Summary

All Methods Static Methods Instance Methods Abstract Methods Concrete Methods
Modifier and Type	Method and Description
`static Params`	`clear(Param<?> param)`
`FPGrowth`	`copy(ParamMap extra)` Creates a copy of this instance with the same UID and some extra params.
`static String`	`explainParam(Param<?> param)`
`static String`	`explainParams()`
`static ParamMap`	`extractParamMap()`
`static ParamMap`	`extractParamMap(ParamMap extra)`
`FPGrowthModel`	`fit(Dataset<?> dataset)` Fits a model to the input data.
`static <T> scala.Option<T>`	`get(Param<T> param)`
`static <T> scala.Option<T>`	`getDefault(Param<T> param)`
`static String`	`getItemsCol()`
`String`	`getItemsCol()`
`static double`	`getMinConfidence()`
`double`	`getMinConfidence()`
`static double`	`getMinSupport()`
`double`	`getMinSupport()`
`static int`	`getNumPartitions()`
`int`	`getNumPartitions()`
`static <T> T`	`getOrDefault(Param<T> param)`
`static Param<Object>`	`getParam(String paramName)`
`static String`	`getPredictionCol()`
`static <T> boolean`	`hasDefault(Param<T> param)`
`static boolean`	`hasParam(String paramName)`
`static boolean`	`isDefined(Param<?> param)`
`static boolean`	`isSet(Param<?> param)`
`static Param<String>`	`itemsCol()`
`Param<String>`	`itemsCol()` Items column name.
`static FPGrowth`	`load(String path)`
`static DoubleParam`	`minConfidence()`
`DoubleParam`	`minConfidence()` Minimal confidence for generating Association Rule.
`static DoubleParam`	`minSupport()`
`DoubleParam`	`minSupport()` Minimal support level of the frequent pattern.
`static IntParam`	`numPartitions()`
`IntParam`	`numPartitions()` Number of partitions (at least 1) used by parallel FP-growth.
`static Param<?>[]`	`params()`
`static Param<String>`	`predictionCol()`
`static void`	`save(String path)`
`static <T> Params`	`set(Param<T> param, T value)`
`FPGrowth`	`setItemsCol(String value)`
`FPGrowth`	`setMinConfidence(double value)`
`FPGrowth`	`setMinSupport(double value)`
`FPGrowth`	`setNumPartitions(int value)`
`FPGrowth`	`setPredictionCol(String value)`
`static String`	`toString()`
`StructType`	Developer API`transformSchema(StructType schema)`
`String`	`uid()` An immutable unique ID for the object and its derivatives.
`StructType`	`validateAndTransformSchema(StructType schema)` Validates and transforms the input schema.
`static MLWriter`	`write()`

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.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)
```
  - toString
```
public static String toString()
```
  - params
```
public static Param<?>[] params()
```
  - explainParam
```
public static String explainParam(Param<?> param)
```
  - explainParams
```
public static String explainParams()
```
  - isSet
```
public static final boolean isSet(Param<?> param)
```
  - isDefined
```
public static final boolean isDefined(Param<?> param)
```
  - hasParam
```
public static boolean hasParam(String paramName)
```
  - getParam
```
public static Param<Object> getParam(String paramName)
```
  - set
```
public static final <T> Params set(Param<T> param,
                                   T value)
```
  - get
```
public static final <T> scala.Option<T> get(Param<T> param)
```
  - clear
```
public static final Params clear(Param<?> param)
```
  - getOrDefault
```
public static final <T> T getOrDefault(Param<T> param)
```
  - getDefault
```
public static final <T> scala.Option<T> getDefault(Param<T> param)
```
  - hasDefault
```
public static final <T> boolean hasDefault(Param<T> param)
```
  - extractParamMap
```
public static final ParamMap extractParamMap(ParamMap extra)
```
  - extractParamMap
```
public static final ParamMap extractParamMap()
```
  - predictionCol
```
public static final Param<String> predictionCol()
```
  - getPredictionCol
```
public static final String getPredictionCol()
```
  - itemsCol
```
public static Param<String> itemsCol()
```
  - getItemsCol
```
public static String getItemsCol()
```
  - minSupport
```
public static DoubleParam minSupport()
```
  - getMinSupport
```
public static double getMinSupport()
```
  - numPartitions
```
public static IntParam numPartitions()
```
  - getNumPartitions
```
public static int getNumPartitions()
```
  - minConfidence
```
public static DoubleParam minConfidence()
```
  - getMinConfidence
```
public static double getMinConfidence()
```
  - save
```
public static void save(String path)
                 throws java.io.IOException
```
    Throws:
    
    java.io.IOException
  - write
```
public static MLWriter write()
```
  - 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)
  - Developer API
    transformSchema
```
public StructType transformSchema(StructType schema)
```
    Description copied from class: PipelineStage
    
    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)
  - itemsCol
```
public Param<String> itemsCol()
```
    Items column name. Default: "items"
    
    Returns:
    
    (undocumented)
  - getItemsCol
```
public String getItemsCol()
```
  - minSupport
```
public DoubleParam minSupport()
```
    Minimal support level of the frequent pattern. [0.0, 1.0]. Any pattern that appears more than (minSupport * size-of-the-dataset) times will be output in the frequent itemsets. Default: 0.3
    
    Returns:
    
    (undocumented)
  - getMinSupport
```
public double getMinSupport()
```
  - numPartitions
```
public IntParam numPartitions()
```
    Number of partitions (at least 1) used by parallel FP-growth. By default the param is not set, and partition number of the input dataset is used.
    
    Returns:
    
    (undocumented)
  - getNumPartitions
```
public int getNumPartitions()
```
  - minConfidence
```
public DoubleParam minConfidence()
```
    Minimal confidence for generating Association Rule. minConfidence will not affect the mining for frequent itemsets, but will affect the association rules generation. Default: 0.8
    
    Returns:
    
    (undocumented)
  - getMinConfidence
```
public double getMinConfidence()
```
  - validateAndTransformSchema
```
public StructType validateAndTransformSchema(StructType schema)
```
    Validates and transforms the input schema.
    
    Parameters:
    
    schema - input schema
    
    Returns:
    
    output schema

Class FPGrowth

Constructor Summary

Method Summary

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

Methods inherited from class Object

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

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

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

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

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

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

Constructor Detail

FPGrowth

FPGrowth

Method Detail

load

toString

params

explainParam

explainParams

isSet

isDefined

hasParam

getParam

set

get

clear

getOrDefault

getDefault

hasDefault

extractParamMap

extractParamMap

predictionCol

getPredictionCol

itemsCol

getItemsCol

minSupport

getMinSupport

numPartitions

getNumPartitions

minConfidence

getMinConfidence

save

write

uid

setMinSupport

setNumPartitions

setMinConfidence

setItemsCol

setPredictionCol

fit

transformSchema

copy

itemsCol

getItemsCol

minSupport

getMinSupport

numPartitions

getNumPartitions

minConfidence

getMinConfidence

validateAndTransformSchema