GoogleUnigram

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. def finalize(): Unit

   

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

   

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10. def getDepLabelNormalizedDistribution(token: PostaggedToken, ngramMap: Map[String, Seq[NgramInfo]], frequencyCutoff: Int): Map[String, Double]

    

    Looks up specified ngramMap for the given token and returns a map of the frequency for each dependency label for the given token word and POS, normalized over the total frequency for all possible dependency labels.

    Looks up specified ngramMap for the given token and returns a map of the frequency for each dependency label for the given token word and POS, normalized over the total frequency for all possible dependency labels.

    token

    the token to look up

    ngramMap

    the table mapping a word to the sequence of NgramInfos, as obtained from the GoogleNGram class object

    frequencyCutoff

    the frequency cutoff that was used to construct the map. This is used here to shift the scale of the frequencies to start from the cutoff point instead of 1.

11. def getFrequencyBucketForFeature(frequency: Double): String

    

    Method to bucketize a given normalized frequency for feature generation.

12. def getPosTagNormalizedDistribution(word: String, ngramMap: Map[String, Seq[NgramInfo]], frequencyCutoff: Int): Map[String, Double]

    

    Looks up specified ngramMap for the given word and returns a map of the frequency for each POS tag for the given word, normalized over the total frequency for all possible POS tags.

    Looks up specified ngramMap for the given word and returns a map of the frequency for each POS tag for the given word, normalized over the total frequency for all possible POS tags.

    word

    the word to look up

    ngramMap

    the table mapping a word to the sequence of NgramInfos, as obtained from the GoogleNGram class object

    frequencyCutoff

    the frequency cutoff that was used to construct the map. This is used here to shift the scale of the frequencies to start from the cutoff point instead of 1.

13. def hashCode(): Int

    

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14. final def isInstanceOf[T0]: Boolean

    

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

    

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16. final def notify(): Unit

    

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17. final def notifyAll(): Unit

    

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

    

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19. def toString(): String

    

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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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