Package org.apache.spark.ml.feature

Class VarianceThresholdSelectorModel

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

  • Method Details

    • read

      public static MLReader<VarianceThresholdSelectorModel> read()

    • load

      public static VarianceThresholdSelectorModel load(String path)

    • varianceThreshold

      public final DoubleParam varianceThreshold()
      Specified by:
      varianceThreshold in interface org.apache.spark.ml.feature.VarianceThresholdSelectorParams

    • outputCol

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

    • featuresCol

      public final Param<String> featuresCol()
      Description copied from interface: HasFeaturesCol
      Param for features column name.
      Specified by:
      featuresCol in interface HasFeaturesCol
      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)

    • selectedFeatures

      public int[] selectedFeatures()

    • setFeaturesCol

      public VarianceThresholdSelectorModel setFeaturesCol(String value)

    • setOutputCol

      public VarianceThresholdSelectorModel 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 VarianceThresholdSelectorModel 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<VarianceThresholdSelectorModel>
      Parameters:
      extra - (undocumented)
      Returns:
      (undocumented)

    • 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