Package opennlp.tools.ml.naivebayes

# Class Probabilities<T>

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

Type Parameters:
  `T` - The label (category) class.

Direct Known Subclasses:
  `LogProbabilities`

public abstract class Probabilities<T> extends Object
Class implementing the probability distribution over labels returned by a classifier.

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `Probabilities()`

- ## 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`
  `getConfidence()`
  `Set<T>`
  `getKeys()`
  `Double`
  `getLog(T t)`
  `T`
  `getMax()`
  `double`
  `getMaxValue()`
  `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`
  `setConfidence(double confidence)`
  Sets the best confidence with which this set of probabilities has been calculated.
  `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.
  `String`
  `toString()`

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

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

- ## Constructor Details

  - ### Probabilities

    public Probabilities()

- ## Method Details

  - ### set

    public void set(T t, double probability)
    Assigns a probability to a label `t`, discarding any previously assigned probability.
    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.
    Parameters:
      `t` - The label to which the probability is being assigned.
      `probability` - The probability 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.
    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.
    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.
    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)
    Parameters:
      `t` - The label whose probability needs to be returned.
    Returns:
      Retrieves the probability associated with the label.

  - ### getLog

    public Double getLog(T t)
    Parameters:
      `t` - The label whose log probability should be returned.
    Returns:
      Retrieves the log probability associated with the label

  - ### getKeys

    public Set<T> getKeys()
    Returns:
      Retrieves the probabilities associated with all labels

  - ### getAll

    public Map<T,Double> getAll()
    Returns:
      Retrieves a `Map` of labels and their probabilities

  - ### getMax

    public T getMax()
    Returns:
      Retrieves the label that has the highest associated probability.

  - ### getMaxValue

    public double getMaxValue()
    Returns:
      Retrieves the probability of the most likely label

  - ### discardCountsBelow

    public void discardCountsBelow(double i)

  - ### getConfidence

    public double getConfidence()
    Returns:
      Retrieves the best confidence with which this set of probabilities has been calculated. This is a function of the amount of data that supports the assertion. It is also a measure of the accuracy of the estimator of the probability.

  - ### setConfidence

    public void setConfidence(double confidence)
    Sets the best confidence with which this set of probabilities has been calculated. This is a function of the amount of data that supports the assertion. It is also a measure of the accuracy of the estimator of the probability.
    Parameters:
      `confidence` - The confidence in the probabilities.

  - ### toString

    public String toString()
    Overrides:
      `toString` in class `Object`