Class

com.salesforce.op.dsl.RichMapFeature

RichBase64MapFeature

Related Doc: package RichMapFeature

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implicit class RichBase64MapFeature extends AnyRef

Enrichment functions for Base64Map features.

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Instance Constructors

  1. new RichBase64MapFeature(f: FeatureLike[Base64Map])

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    f

    FeatureLike

Value Members

  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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  6. def detectMimeTypes(typeHint: Option[String] = None): FeatureLike[PickListMap]

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    Detect MIME type for Base64Map encoded binary data

    Detect MIME type for Base64Map encoded binary data

    typeHint

    MIME type hint, i.e. 'application/json', 'text/plain' etc.

    returns

    mime type as text

  7. final def eq(arg0: AnyRef): Boolean

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  8. def equals(arg0: Any): Boolean

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  9. val f: FeatureLike[Base64Map]

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    FeatureLike

  10. def finalize(): Unit

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  11. final def getClass(): Class[_]

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  12. def hashCode(): Int

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  13. final def isInstanceOf[T0]: Boolean

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  14. final def ne(arg0: AnyRef): Boolean

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. final def synchronized[T0](arg0: ⇒ T0): T0

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  18. def toString(): String

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  19. def vectorize(topK: Int, minSupport: Int, cleanText: Boolean, cleanKeys: Boolean = TransmogrifierDefaults.CleanKeys, whiteListKeys: Array[String] = Array.empty, blackListKeys: Array[String] = Array.empty, typeHint: Option[String] = None, trackNulls: Boolean = TransmogrifierDefaults.TrackNulls, others: Array[FeatureLike[Base64Map]] = Array.empty, maxPctCardinality: Double = ...): FeatureLike[OPVector]

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    Base64Map vecrtorization: MIME types are extracted, and the maps are converted into PickListMaps and then vectorized using the TextMapPivotVectorizer.

    Base64Map vecrtorization: MIME types are extracted, and the maps are converted into PickListMaps and then vectorized using the TextMapPivotVectorizer.

    topK

    number of values to keep for each key

    minSupport

    min times a value must occur to be retained in pivot

    cleanText

    clean text before pivoting

    cleanKeys

    clean map keys before pivoting

    whiteListKeys

    keys to whitelist

    blackListKeys

    keys to blacklist

    typeHint

    optional hint for MIME type detector

    trackNulls

    option to keep track of values that were missing

    others

    other features of the same type

    maxPctCardinality

    max percentage of distinct values a categorical feature can have (between 0.0 and 1.00)

    returns

    an OPVector feature

  20. final def wait(): Unit

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  21. final def wait(arg0: Long, arg1: Int): Unit

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  22. final def wait(arg0: Long): Unit

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