opennlp.tools.ml.model.Prior Maven / Gradle / Ivy
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package opennlp.tools.ml.model;
/**
* This interface allows one to implement a prior distribution for use in
* maximum entropy model training.
*/
public interface Prior {
/**
* Populates the specified array with the 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.
* @param dist An array to be populated with the log of the prior distribution.
* @param context The indices of the contextual predicates for an event.
*/
void logPrior(double[] dist, int[] context);
/**
* Populates the specified array with the 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.
* @param dist An array to be populated with the log of the prior distribution.
* @param context The indices of the contextual predicates for an event.
* @param values The values associated with the context.
*/
void logPrior(double[] dist, int[] context, float[] values);
/**
* Populates the specified array with the 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.
* @param dist An array to be populated with the log of the prior distribution.
* @param context The indices of the contextual predicates for an event.
* @param values The values associated with the context.
*/
void logPrior(double[] dist, Context[] context, float[] values);
/**
* 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 #logPrior.
* @param outcomeLabels An array of each outcome label.
* @param contextLabels An array of each context label.
*/
void setLabels(String[] outcomeLabels, String[] contextLabels);
}