Package opennlp.tools.ngram

## Class NGramUtils

- java.lang.Object
- - opennlp.tools.ngram.NGramUtils

-     public class NGramUtils
      extends Object

  Utility class for ngrams. Some methods apply specifically to certain 'n' values, for e.g. tri/bi/uni-grams.

- - ### Constructor Summary

    Constructors
    Constructor | Description
    --- | ---
    `NGramUtils()` |

  - ### Method Summary

    All Methods Static Methods Concrete Methods
    Modifier and Type | Method | Description
    --- | --- | ---
    `static double` | `calculateBigramMLProbability​(String x0, String x1, Collection<StringList> set)` | calculate the probability of a bigram in a vocabulary using maximum likelihood estimation
    `static double` | `calculateBigramPriorSmoothingProbability​(String x0, String x1, Collection<StringList> set, Double k)` | calculate the probability of a bigram in a vocabulary using prior Laplace smoothing algorithm
    `static double` | `calculateLaplaceSmoothingProbability​(StringList ngram, Iterable<StringList> set, Double k)` | calculate the probability of a ngram in a vocabulary using Laplace smoothing algorithm
    `static double` | `calculateMissingNgramProbabilityMass​(StringList ngram, double discount, Iterable<StringList> set)` | calculate the probability of a ngram in a vocabulary using the missing probability mass algorithm
    `static double` | `calculateNgramMLProbability​(StringList ngram, Iterable<StringList> set)` | calculate the probability of a ngram in a vocabulary using maximum likelihood estimation
    `static double` | `calculateTrigramLinearInterpolationProbability​(String x0, String x1, String x2, Collection<StringList> set, Double lambda1, Double lambda2, Double lambda3)` | calculate the probability of a trigram in a vocabulary using a linear interpolation algorithm
    `static double` | `calculateTrigramMLProbability​(String x0, String x1, String x2, Iterable<StringList> set)` | calculate the probability of a trigram in a vocabulary using maximum likelihood estimation
    `static double` | `calculateUnigramMLProbability​(String word, Collection<StringList> set)` | calculate the probability of a unigram in a vocabulary using maximum likelihood estimation
    `static Collection<String[]>` | `getNGrams​(String[] sequence, int size)` | Get the ngrams of dimension n of a certain input sequence of tokens.
    `static Collection<StringList>` | `getNGrams​(StringList sequence, int size)` | Get the ngrams of dimension n of a certain input sequence of tokens.
    `static StringList` | `getNMinusOneTokenFirst​(StringList ngram)` | get the (n-1)th ngram of a given ngram, that is the same ngram except the last word in the ngram
    `static StringList` | `getNMinusOneTokenLast​(StringList ngram)` | get the (n-1)th ngram of a given ngram, that is the same ngram except the first word in the ngram

    - ### Methods inherited from class java.lang.Object

      `equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait`

- - ### Constructor Detail

    - #### NGramUtils

          public NGramUtils()

  - ### Method Detail

    - #### calculateLaplaceSmoothingProbability

          public static double calculateLaplaceSmoothingProbability​(StringList ngram,
                                                                    Iterable<StringList> set,
                                                                    Double k)

      calculate the probability of a ngram in a vocabulary using Laplace smoothing algorithm
      Parameters:
        `ngram` - the ngram to get the probability for
        `set` - the vocabulary
        `k` - the smoothing factor
      Returns:
        the Laplace smoothing probability
      See Also:
        Additive Smoothing

    - #### calculateUnigramMLProbability

          public static double calculateUnigramMLProbability​(String word,
                                                             Collection<StringList> set)

      calculate the probability of a unigram in a vocabulary using maximum likelihood estimation
      Parameters:
        `word` - the only word in the unigram
        `set` - the vocabulary
      Returns:
        the maximum likelihood probability

    - #### calculateBigramMLProbability

          public static double calculateBigramMLProbability​(String x0,
                                                            String x1,
                                                            Collection<StringList> set)

      calculate the probability of a bigram in a vocabulary using maximum likelihood estimation
      Parameters:
        `x0` - first word in the bigram
        `x1` - second word in the bigram
        `set` - the vocabulary
      Returns:
        the maximum likelihood probability

    - #### calculateTrigramMLProbability

          public static double calculateTrigramMLProbability​(String x0,
                                                             String x1,
                                                             String x2,
                                                             Iterable<StringList> set)

      calculate the probability of a trigram in a vocabulary using maximum likelihood estimation
      Parameters:
        `x0` - first word in the trigram
        `x1` - second word in the trigram
        `x2` - third word in the trigram
        `set` - the vocabulary
      Returns:
        the maximum likelihood probability

    - #### calculateNgramMLProbability

          public static double calculateNgramMLProbability​(StringList ngram,
                                                           Iterable<StringList> set)

      calculate the probability of a ngram in a vocabulary using maximum likelihood estimation
      Parameters:
        `ngram` - a ngram
        `set` - the vocabulary
      Returns:
        the maximum likelihood probability

    - #### calculateBigramPriorSmoothingProbability

          public static double calculateBigramPriorSmoothingProbability​(String x0,
                                                                        String x1,
                                                                        Collection<StringList> set,
                                                                        Double k)

      calculate the probability of a bigram in a vocabulary using prior Laplace smoothing algorithm
      Parameters:
        `x0` - the first word in the bigram
        `x1` - the second word in the bigram
        `set` - the vocabulary
        `k` - the smoothing factor
      Returns:
        the prior Laplace smoothing probability

    - #### calculateTrigramLinearInterpolationProbability

          public static double calculateTrigramLinearInterpolationProbability​(String x0,
                                                                              String x1,
                                                                              String x2,
                                                                              Collection<StringList> set,
                                                                              Double lambda1,
                                                                              Double lambda2,
                                                                              Double lambda3)

      calculate the probability of a trigram in a vocabulary using a linear interpolation algorithm
      Parameters:
        `x0` - the first word in the trigram
        `x1` - the second word in the trigram
        `x2` - the third word in the trigram
        `set` - the vocabulary
        `lambda1` - trigram interpolation factor
        `lambda2` - bigram interpolation factor
        `lambda3` - unigram interpolation factor
      Returns:
        the linear interpolation probability

    - #### calculateMissingNgramProbabilityMass

          public static double calculateMissingNgramProbabilityMass​(StringList ngram,
                                                                    double discount,
                                                                    Iterable<StringList> set)

      calculate the probability of a ngram in a vocabulary using the missing probability mass algorithm
      Parameters:
        `ngram` - the ngram
        `discount` - discount factor
        `set` - the vocabulary
      Returns:
        the probability

    - #### getNMinusOneTokenFirst

          public static StringList getNMinusOneTokenFirst​(StringList ngram)

      get the (n-1)th ngram of a given ngram, that is the same ngram except the last word in the ngram
      Parameters:
        `ngram` - a ngram
      Returns:
        a ngram

    - #### getNMinusOneTokenLast

          public static StringList getNMinusOneTokenLast​(StringList ngram)

      get the (n-1)th ngram of a given ngram, that is the same ngram except the first word in the ngram
      Parameters:
        `ngram` - a ngram
      Returns:
        a ngram

    - #### getNGrams

          public static Collection<StringList> getNGrams​(StringList sequence,
                                                         int size)

      Get the ngrams of dimension n of a certain input sequence of tokens.
      Parameters:
        `sequence` - a sequence of tokens
        `size` - the size of the resulting ngrmams
      Returns:
        all the possible ngrams of the given size derivable from the input sequence

    - #### getNGrams

          public static Collection<String[]> getNGrams​(String[] sequence,
                                                       int size)

      Get the ngrams of dimension n of a certain input sequence of tokens.
      Parameters:
        `sequence` - a sequence of tokens
        `size` - the size of the resulting ngrmams
      Returns:
        all the possible ngrams of the given size derivable from the input sequence