Class Prediction<T extends Output<T>>

java.lang.Object
org.tribuo.Prediction<T>
All Implemented Interfaces:
Serializable
public class Prediction<T extends Output<T>> extends Object implements Serializable
A prediction made by a Model. Contains the output, and optionally and a map of scores over the possible outputs. If hasProbabilities() == true then it has a probability distribution over outputs otherwise it is unnormalized scores over outputs.

If possible it also contains the number of features that were used to make a prediction, and how many features originally existed in the Example.

See Also:

  • Constructor Details

    • Prediction

      public Prediction(T output, Map<String,T> outputScores, int numUsed, Example<T> example, boolean probability)
      Constructs a prediction from the supplied arguments.
      Parameters:
      output - The predicted output (i.e., the one with the maximum score).
      outputScores - The output score distribution.
      numUsed - The number of features used to make the prediction.
      example - The input example.
      probability - Are the scores probabilities?

    • Prediction

      public Prediction(T output, int numUsed, Example<T> example)
      Constructs a prediction from the supplied arguments.
      Parameters:
      output - The predicted output.
      numUsed - The number of features used to make the prediction.
      example - The input example.

    • Prediction

      public Prediction(Prediction<T> other, int numUsed, Example<T> example)
      Constructs a prediction from the supplied arguments.
      Parameters:
      other - The prediction to copy.
      numUsed - The number of features used to make the prediction.
      example - The input example.

  • Method Details

    • getOutput

      public T getOutput()
      Returns the predicted output.
      Returns:
      The predicted output.

    • getNumActiveFeatures

      public int getNumActiveFeatures()
      Returns the number of features used in the prediction.
      Returns:
      The number of features used.

    • getExampleSize

      public int getExampleSize()
      Returns the number of features in the example.
      Returns:
      The number of features in the example.

    • getExample

      public Example<T> getExample()
      Returns the example itself.
      Returns:
      The example.

    • getOutputScores

      public Map<String,T> getOutputScores()
      Gets the output scores for each output.

      May be an empty map if it did not generate scores.

      Returns:
      A Map.

    • hasProbabilities

      public boolean hasProbabilities()
      Are the scores probabilities?
      Returns:
      True if the scores are probabilities.

    • toString

      public String toString()
      Overrides:
      toString in class Object