Package org.apache.spark.ml.feature

Class IDFModel

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.Model<IDFModel>
org.apache.spark.ml.feature.IDFModel
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, IDFBase, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable
public class IDFModel extends Model<IDFModel> implements IDFBase, MLWritable
Model fitted by IDF.
See Also:

  • Method Details

    • read

      public static MLReader<IDFModel> read()

    • load

      public static IDFModel load(String path)

    • 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 IDFModel setInputCol(String value)

    • setOutputCol

      public IDFModel setOutputCol(String value)

    • transform

      public Dataset<Row> transform(Dataset<?> dataset)
      Description copied from class: Transformer
      Transforms the input dataset.
      Specified by:
      transform in class Transformer
      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 IDFModel 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 Model<IDFModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)

    • idf

      public Vector idf()
      Returns the IDF vector.

    • docFreq

      public long[] docFreq()
      Returns the document frequency

    • numDocs

      public long numDocs()
      Returns number of documents evaluated to compute idf

    • write

      public MLWriter write()
      Description copied from interface: MLWritable
      Returns an MLWriter instance for this ML instance.
      Specified by:
      write in interface MLWritable
      Returns:
      (undocumented)

    • toString

      public String toString()
      Specified by:
      toString in interface Identifiable
      Overrides:
      toString in class Object