Class FPGrowth

All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, org.apache.spark.ml.fpm.FPGrowthParams, Params, HasPredictionCol, DefaultParamsWritable, Identifiable, MLWritable

public class FPGrowth extends Estimator<FPGrowthModel> implements org.apache.spark.ml.fpm.FPGrowthParams, 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:
  • Constructor Details

    • FPGrowth

      public FPGrowth(String uid)
    • FPGrowth

      public FPGrowth()
  • Method Details

    • load

      public static FPGrowth load(String path)
    • read

      public static MLReader<T> read()
    • itemsCol

      public Param<String> itemsCol()
      Specified by:
      itemsCol in interface org.apache.spark.ml.fpm.FPGrowthParams
    • minSupport

      public DoubleParam minSupport()
      Specified by:
      minSupport in interface org.apache.spark.ml.fpm.FPGrowthParams
    • numPartitions

      public IntParam numPartitions()
      Specified by:
      numPartitions in interface org.apache.spark.ml.fpm.FPGrowthParams
    • minConfidence

      public DoubleParam minConfidence()
      Specified by:
      minConfidence in interface org.apache.spark.ml.fpm.FPGrowthParams
    • predictionCol

      public final Param<String> predictionCol()
      Description copied from interface: HasPredictionCol
      Param for prediction column name.
      Specified by:
      predictionCol in interface HasPredictionCol
      Returns:
      (undocumented)
    • 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
      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)