Package org.apache.spark.ml.feature

Class PCAModel

Object
org.apache.spark.ml.PipelineStage
org.apache.spark.ml.Transformer
org.apache.spark.ml.Model<PCAModel>
org.apache.spark.ml.feature.PCAModel
All Implemented Interfaces:
Serializable, org.apache.spark.internal.Logging, PCAParams, Params, HasInputCol, HasOutputCol, Identifiable, MLWritable
public class PCAModel extends Model<PCAModel> implements PCAParams, MLWritable
Model fitted by PCA. Transforms vectors to a lower dimensional space.

param: pc A principal components Matrix. Each column is one principal component. param: explainedVariance A vector of proportions of variance explained by each principal component.

See Also:

  • Method Details

    • read

      public static MLReader<PCAModel> read()

    • load

      public static PCAModel load(String path)

    • k

      public final IntParam k()
      Description copied from interface: PCAParams
      The number of principal components.
      Specified by:
      k in interface PCAParams
      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)

    • pc

      public DenseMatrix pc()

    • explainedVariance

      public DenseVector explainedVariance()

    • setInputCol

      public PCAModel setInputCol(String value)

    • setOutputCol

      public PCAModel setOutputCol(String value)

    • transform

      public Dataset<Row> transform(Dataset<?> dataset)
      Transform a vector by computed Principal Components.

      Specified by:
      transform in class Transformer
      Parameters:
      dataset - (undocumented)
      Returns:
      (undocumented)
      Note:
      Vectors to be transformed must be the same length as the source vectors given to PCA.fit().

    • 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 PCAModel 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<PCAModel>
      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