Package opennlp.tools.ml.naivebayes

# Class LogProbabilities<T>

java.lang.Object
opennlp.tools.ml.naivebayes.Probabilities<T>
opennlp.tools.ml.naivebayes.LogProbabilities<T>

Type Parameters:
  `T` - the label (category) class

public class LogProbabilities<T> extends Probabilities<T>
Class implementing the probability distribution over labels returned by a classifier as a log of probabilities.

This is necessary because floating point precision in Java does not allow for high-accuracy representation of very low probabilities such as would occur in a text categorizer.

See Also:
  - `Probabilities`

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `LogProbabilities()`

- ## Method Summary

  Modifier and Type
  Method
  Description
  `void`
  `addIn(T t, double probability, int count)`
  Compounds the existing `probability` mass on the label `t` with the new probability passed in to the method.
  `void`
  `discardCountsBelow(double i)`
  `Double`
  `get(T t)`
  `Map<T,Double>`
  `getAll()`
  `Double`
  `getLog(T t)`
  `T`
  `getMax()`
  `void`
  `set(T t, double probability)`
  Assigns a `probability` to a label `t`, discarding any previously assigned probability.
  `void`
  `set(T t, Probability<T> probability)`
  Assigns a `probability` to a label `t`, discarding any previously assigned probability.
  `void`
  `setIfLarger(T t, double probability)`
  Assigns a `probability` to a label `t`, discarding any previously assigned probability, if the new probability is greater than the old one.
  `void`
  `setLog(T t, double probability)`
  Assigns a log `probability` to a label `t`, discarding any previously assigned probability.

  ### Methods inherited from class opennlp.tools.ml.naivebayes.Probabilities

  `getConfidence, getKeys, getMaxValue, setConfidence, toString`

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

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

- ## Constructor Details

  - ### LogProbabilities

    public LogProbabilities()

- ## Method Details

  - ### set

    public void set(T t, double probability)
    Assigns a `probability` to a label `t`, discarding any previously assigned probability.
    Overrides:
      `set` in class `Probabilities<T>`
    Parameters:
      `t` - The label to which the probability is being assigned.
      `probability` - The probability to assign.

  - ### set

    public void set(T t, Probability<T> probability)
    Assigns a `probability` to a label `t`, discarding any previously assigned probability.
    Overrides:
      `set` in class `Probabilities<T>`
    Parameters:
      `t` - The label to which the probability is being assigned.
      `probability` - The `Probability<T>` to assign.

  - ### setIfLarger

    public void setIfLarger(T t, double probability)
    Assigns a `probability` to a label `t`, discarding any previously assigned probability, if the new probability is greater than the old one.
    Overrides:
      `setIfLarger` in class `Probabilities<T>`
    Parameters:
      `t` - The label to which the probability is being assigned.
      `probability` - The probability to assign.

  - ### setLog

    public void setLog(T t, double probability)
    Assigns a log `probability` to a label `t`, discarding any previously assigned probability.
    Overrides:
      `setLog` in class `Probabilities<T>`
    Parameters:
      `t` - The label to which the log probability is being assigned.
      `probability` - The log `probability` to assign.

  - ### addIn

    public void addIn(T t, double probability, int count)
    Compounds the existing `probability` mass on the label `t` with the new probability passed in to the method.
    Overrides:
      `addIn` in class `Probabilities<T>`
    Parameters:
      `t` - The label whose `probability` mass is being updated.
      `probability` - The probability weight to add.
      `count` - The amplifying factor for the `probability` compounding.

  - ### get

    public Double get(T t)
    Overrides:
      `get` in class `Probabilities<T>`
    Parameters:
      `t` - The label whose probability shall be returned.
    Returns:
      Retrieves the probability associated with the label `t`.

  - ### getLog

    public Double getLog(T t)
    Overrides:
      `getLog` in class `Probabilities<T>`
    Parameters:
      `t` - The label whose log probability shall be returned.
    Returns:
      Retrieves the log probability associated with the label `t`.

  - ### discardCountsBelow

    public void discardCountsBelow(double i)
    Overrides:
      `discardCountsBelow` in class `Probabilities<T>`

  - ### getAll

    public Map<T,Double> getAll()
    Overrides:
      `getAll` in class `Probabilities<T>`
    Returns:
      Retrieves a `Map` of all labels and their probabilities.

  - ### getMax

    public T getMax()
    Overrides:
      `getMax` in class `Probabilities<T>`
    Returns:
      Retrieves the label that has the highest associated probability