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

CountVectorizer (Spark 4.0.0 JavaDoc)

All Implemented Interfaces:

Serializable, org.apache.spark.internal.Logging, CountVectorizerParams, Params, HasInputCol, HasOutputCol, DefaultParamsWritable, Identifiable, MLWritable

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

• Constructor Summary

  Constructors

• Method Summary

  Binary toggle to control the output vector values.

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

  Fits a model to the input data.

  Param for input column name.

  Specifies the maximum number of different documents a term could appear in to be included in the vocabulary.

  Specifies the minimum number of different documents a term must appear in to be included in the vocabulary.

  Filter to ignore rare words in a document.

  Param for output column name.

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

  An immutable unique ID for the object and its derivatives.

  Max size of the vocabulary.

  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

• Constructor Details
  • CountVectorizer public CountVectorizer(String uid)
  • CountVectorizer

    public CountVectorizer()

• Method Details
  • load
  • read
  • vocabSize

    Default: 2^18^

    Specified by:

    vocabSize in interface CountVectorizerParams

    Returns:

    (undocumented)

  • minDF

    Default: 1.0

    Specified by:

    minDF in interface CountVectorizerParams

    Returns:

    (undocumented)

  • maxDF

    Default: (2^63^) - 1

    Specified by:

    maxDF in interface CountVectorizerParams

    Returns:

    (undocumented)

  • minTF

    Filter to ignore rare words in a document. For each document, terms with frequency/count less than the given threshold are ignored. If this is an integer greater than or equal to 1, then this specifies a count (of times the term must appear in the document); if this is a double in [0,1), then this specifies a fraction (out of the document's token count).

    Note that the parameter is only used in transform of CountVectorizerModel and does not affect fitting.

    Default: 1.0

    Specified by:

    minTF in interface CountVectorizerParams

    Returns:

    (undocumented)

  • binary

    Binary toggle to control the output vector values. If True, all nonzero counts (after minTF filter applied) are set to 1. This is useful for discrete probabilistic models that model binary events rather than integer counts. Default: false

    Specified by:

    binary in interface CountVectorizerParams

    Returns:

    (undocumented)

  • outputCol

    Param for output column name.

    Specified by:

    outputCol in interface HasOutputCol

    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)

  • setInputCol
  • setOutputCol
  • setVocabSize
  • setMinDF
  • setMaxDF
  • setMinTF
  • setBinary
  • fit

    Fits a model to the input data.

    Specified by:

    fit in class Estimator<CountVectorizerModel>

    Parameters:

    dataset - (undocumented)

    Returns:

    (undocumented)

  • 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)

  • 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 Estimator<CountVectorizerModel>

    Parameters:

    extra - (undocumented)

    Returns:

    (undocumented)

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