RichEmailFeature

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. final def eq(arg0: AnyRef): Boolean

   

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7. def equals(arg0: Any): Boolean

   

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8. val f: FeatureLike[Email]

   

9. def finalize(): Unit

   

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

    

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11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. def isValidEmail: FeatureLike[Binary]

    

    Check if email is valid

    Check if email is valid

    returns

    binary feature containing boolean value of whether email was valid format

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 toEmailDomain: FeatureLike[Text]

    

    Extract email domains

    Extract email domains

    returns

    email domain

19. def toEmailPrefix: FeatureLike[Text]

    

    Extract email prefixes

    Extract email prefixes

    returns

    email prefix

20. def toString(): String

    

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21. def vectorize(topK: Int, cleanText: Boolean, minSupport: Int, trackNulls: Boolean = TransmogrifierDefaults.TrackNulls, others: Array[FeatureLike[Email]] = Array.empty, maxPctCardinality: Double = ...): FeatureLike[OPVector]

    

    Converts a sequence of Email features into a vector, extracting the domains of the e-mails and keeping the top K occurrences of each feature, along with an extra column per feature indicating how many values were not in the top K.

    Converts a sequence of Email features into a vector, extracting the domains of the e-mails and keeping the top K occurrences of each feature, along with an extra column per feature indicating how many values were not in the top K.

    topK

    How many values to keep in the vector

    cleanText

    If true, ignores capitalization and punctuations when grouping categories

    minSupport

    Min times a value must occur to be retained in pivot

    trackNulls

    keep an extra column that indicated if feature was null

    others

    Other Email features

    maxPctCardinality

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

    returns

    The vectorized features

22. final def wait(): Unit

    

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

    

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

    

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