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Showing content from http://spark.apache.org/docs/latest/api/java/org/apache/spark/ml/feature/OneHotEncoderModel.html below:

OneHotEncoderModel (Spark 4.0.0 JavaDoc)

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, OneHotEncoderBase, Params, HasHandleInvalid, HasInputCol, HasInputCols, HasOutputCol, HasOutputCols, Identifiable, MLWritable

param: categorySizes Original number of categories for each feature being encoded. The array contains one value for each input column, in order.

See Also:

• Serialized Form

• Nested Class Summary
  Nested classes/interfaces inherited from interface org.apache.spark.internal.Loggingorg.apache.spark.internal.Logging.LogStringContext, org.apache.spark.internal.Logging.SparkShellLoggingFilter

• Method Summary

  int[]

  Creates a copy of this instance with the same UID and some extra params.

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

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

  Param for input column name.

  Param for input column names.

  Param for output column name.

  Param for output column names.

  Transforms the input dataset.

  Check transform validity and derive the output schema from the input schema.

  An immutable unique ID for the object and its derivatives.

  Returns an MLWriter instance for this ML instance.

  Methods inherited from interface org.apache.spark.internal.LogginginitializeForcefully, initializeLogIfNecessary, initializeLogIfNecessary, initializeLogIfNecessary$default$2, isTraceEnabled, log, logDebug, logDebug, logDebug, logDebug, logError, logError, logError, logError, logInfo, logInfo, logInfo, logInfo, logName, LogStringContext, logTrace, logTrace, logTrace, logTrace, logWarning, logWarning, logWarning, logWarning, org$apache$spark$internal$Logging$$log_, org$apache$spark$internal$Logging$$log__$eq, withLogContext
  Methods inherited from interface org.apache.spark.ml.util.MLWritablesave Methods inherited from interface org.apache.spark.ml.param.Paramsclear, copyValues, defaultCopy, defaultParamMap, explainParam, explainParams, extractParamMap, extractParamMap, get, getDefault, getOrDefault, getParam, hasDefault, hasParam, isDefined, isSet, onParamChange, paramMap, params, set, set, set, setDefault, setDefault, shouldOwn

• Method Details
  • read
  • load
  • 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

    Specified by:

    handleInvalid in interface OneHotEncoderBase

    Returns:

    (undocumented)

  • dropLast

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

    Specified by:

    dropLast in interface OneHotEncoderBase

    Returns:

    (undocumented)

  • outputCols

    Param for output column names.

    Specified by:

    outputCols in interface HasOutputCols

    Returns:

    (undocumented)

  • outputCol

    Param for output column name.

    Specified by:

    outputCol in interface HasOutputCol

    Returns:

    (undocumented)

  • inputCols

    Param for input column names.

    Specified by:

    inputCols in interface HasInputCols

    Returns:

    (undocumented)

  • inputCol

    Param for input column name.

    Specified by:

    inputCol in interface HasInputCol

    Returns:

    (undocumented)

  • uid

    An immutable unique ID for the object and its derivatives.

    Specified by:

    uid in interface Identifiable

    Returns:

    (undocumented)

  • categorySizes

    public int[] categorySizes()

  • setInputCol
  • setOutputCol
  • setInputCols
  • setOutputCols
  • setDropLast
  • setHandleInvalid
  • transformSchema

    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)

  • transform

    Transforms the input dataset.

    Specified by:

    transform in class Transformer

    Parameters:

    dataset - (undocumented)

    Returns:

    (undocumented)

  • copy 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<OneHotEncoderModel>

    Parameters:

    extra - (undocumented)

    Returns:

    (undocumented)

  • write

    Returns an MLWriter instance for this ML instance.

    Specified by:

    write in interface MLWritable

    Returns:

    (undocumented)

  • toString

    Specified by:

    toString in interface Identifiable

    Overrides:

    toString in class Object

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