Package opennlp.tools.ml.model

# Class UniformPrior

java.lang.Object
opennlp.tools.ml.model.UniformPrior

All Implemented Interfaces:
  `Prior`

public class UniformPrior extends Object implements Prior
Provide a maximum entropy model with a uniform `Prior`.

- ## Constructor Summary

  Constructors
  Constructor
  Description
  `UniformPrior()`

- ## Method Summary

  Modifier and Type
  Method
  Description
  `boolean`
  `equals(Object obj)`
  `int`
  `hashCode()`
  `void`
  `logPrior(double[] dist, int[] context)`
  Populates the specified array with the log of the distribution for the specified context.
  `void`
  `logPrior(double[] dist, int[] context, float[] values)`
  Populates the specified array with the log of the distribution for the specified context.
  `void`
  `logPrior(double[] dist, Context[] context, float[] values)`
  Populates the specified array with the log of the distribution for the specified context.
  `void`
  `setLabels(String[] outcomeLabels, String[] contextLabels)`
  Method to specify the label for the outcomes and contexts.

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

  `getClass, notify, notifyAll, toString, wait, wait, wait`

- ## Constructor Details

  - ### UniformPrior

    public UniformPrior()

- ## Method Details

  - ### logPrior

    public void logPrior(double[] dist, int[] context, float[] values)
    Description copied from interface: `Prior`
    Populates the specified array with the log of the distribution for the specified context. The returned array will be overwritten and needs to be re-initialized with every call to this method.
    Specified by:
      `logPrior` in interface `Prior`
    Parameters:
      `dist` - An array to be populated with the log of the prior distribution.
      `context` - The indices of the contextual predicates for an event.
      `values` - The values associated with the context.

  - ### logPrior

    public void logPrior(double[] dist, Context[] context, float[] values)
    Description copied from interface: `Prior`
    Populates the specified array with the log of the distribution for the specified context. The returned array will be overwritten and needs to be re-initialized with every call to this method.
    Specified by:
      `logPrior` in interface `Prior`
    Parameters:
      `dist` - An array to be populated with the log of the prior distribution.
      `context` - The indices of the contextual predicates for an event.
      `values` - The values associated with the context.

  - ### logPrior

    public void logPrior(double[] dist, int[] context)
    Description copied from interface: `Prior`
    Populates the specified array with the log of the distribution for the specified context. The returned array will be overwritten and needs to be re-initialized with every call to this method.
    Specified by:
      `logPrior` in interface `Prior`
    Parameters:
      `dist` - An array to be populated with the log of the prior distribution.
      `context` - The indices of the contextual predicates for an event.

  - ### setLabels

    public void setLabels(String[] outcomeLabels, String[] contextLabels)
    Description copied from interface: `Prior`
    Method to specify the label for the outcomes and contexts. This is used to map integer outcomes and contexts to their string values. This method is called prior to any call to `Prior.logPrior(double[], int[])`.
    Specified by:
      `setLabels` in interface `Prior`
    Parameters:
      `outcomeLabels` - An array of each outcome label.
      `contextLabels` - An array of each context label.

  - ### hashCode

    public int hashCode()
    Overrides:
      `hashCode` in class `Object`

  - ### equals

    public boolean equals(Object obj)
    Overrides:
      `equals` in class `Object`