All Superinterfaces:

HasHandleInvalid, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, Identifiable, Params, Serializable

All Known Implementing Classes:

OneHotEncoder, OneHotEncoderModel

Private trait for params and common methods for OneHotEncoder and OneHotEncoderModel

• Method Summary

  dropLast()

  Whether to drop the last category in the encoded vector (default: true)

  boolean

  Returns the input and output column names corresponding in pair.

  Param for how to handle invalid data during transform().

  validateAndTransformSchema(StructType schema, boolean dropLast, boolean keepInvalid)

  Methods inherited from interface org.apache.spark.ml.param.Params

  clear, copy, copyValues, defaultCopy, defaultParamMap, estimateMatadataSize, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

• Method Details

  • dropLast

    Whether to drop the last category in the encoded vector (default: true)

    Returns:

    (undocumented)

  • getDropLast

    boolean getDropLast()

  • getInOutCols

    Returns the input and output column names corresponding in pair.

  • handleInvalid

    Param for how to handle invalid data during transform(). Options are 'keep' (invalid data presented as an extra categorical feature) or 'error' (throw an error). Note that this Param is only used during transform; during fitting, invalid data will result in an error. Default: "error"

    Specified by:

    handleInvalid in interface HasHandleInvalid

    Returns:

    (undocumented)

  • validateAndTransformSchema

    StructType validateAndTransformSchema(StructType schema, boolean dropLast, boolean keepInvalid)