Package org.apache.spark.ml.feature

Class IDF

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Estimator<IDFModel>
org.apache.spark.ml.feature.IDF
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, IDFBase, Params, HasInputCol, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable
public final class IDF extends Estimator<IDFModel> implements IDFBase, DefaultParamsWritable
Compute the Inverse Document Frequency (IDF) given a collection of documents.
See Also:

  • Constructor Details

    • IDF

      public IDF(String uid)

    • IDF

      public IDF()

  • Method Details

    • load

      public static IDF load(String path)

    • read

      public static MLReader<T> read()

    • minDocFreq

      public final IntParam minDocFreq()
      Description copied from interface: IDFBase
      The minimum number of documents in which a term should appear. Default: 0
      Specified by:
      minDocFreq in interface IDFBase
      Returns:
      (undocumented)

    • outputCol

      public final Param<String> outputCol()
      Description copied from interface: HasOutputCol
      Param for output column name.
      Specified by:
      outputCol in interface HasOutputCol
      Returns:
      (undocumented)

    • inputCol

      public final Param<String> inputCol()
      Description copied from interface: HasInputCol
      Param for input column name.
      Specified by:
      inputCol in interface HasInputCol
      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)

    • setInputCol

      public IDF setInputCol(String value)

    • setOutputCol

      public IDF setOutputCol(String value)

    • setMinDocFreq

      public IDF setMinDocFreq(int value)

    • fit

      public IDFModel fit(Dataset<?> dataset)
      Description copied from class: Estimator
      Fits a model to the input data.
      Specified by:
      fit in class Estimator<IDFModel>
      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 IDF 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<IDFModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)