prediction.java

Boosting算法软件包

package jboost.booster;

import java.io.Serializable;

import jboost.examples.Label;

/**
 * This is the abstract definition of a prediction.
 * A prediction is an abstract object representing the output of base
 * classifier.  Predictions can be added or multiplied by scalars.
 * They also can be converted to an interpretable form 
 * (index of the best class or a real-valued score for each class)
 */
public abstract class Prediction implements Serializable{

  /*
   * Creates a clone of this.
   */
   public abstract Object clone();

  /**
   * Adds another prediction object to this one. (changes object)
   */
    public abstract Prediction add(Prediction p);

    
    /**
     * Returns true iff this prediction is normalized
     */
    public static boolean isNormPred(Prediction p) {
        return (p instanceof NormalizedPrediction);
    }
    

  /**
   * Multiplies this by a scalar and returns it. (changes object)
   */
  public abstract Prediction scale(double w);

  /**
   * Adds a given scalar times a given prediction object to this one.
   * (changes object) */
    public abstract Prediction add(double w, Prediction p);

    /**
     * Converts this to a vector of "scores" for each class (where
     * higher is better).
     */
    public abstract double[] getClassScores();

    /**
     * Computes the "margins" for this prediction relative to a given
     * "correct" label.  The margin need not be normalized to
     * lie in [-1,+1].  Note that several margin values may be
     * returned for each example.
     *
     * @param label the "correct" label
     * @return the computed margin */
    public abstract double[] getMargins(Label label);


    /** generate a short textual representation (shorter than "toString")*/
    public abstract String shortText();
    
    /**
     * Check to see if two Predictions are equivalent
     * @param other
     * @return true if this Prediction is the same as the other
     */
    public abstract boolean equals(Prediction other);
    
    
    /**
     * Returns the class with the highest score.  In case of ties, a
     * label with multiple values is returned.
     */
    public Label getBestClass() {
	double[] scores = getClassScores();
	double max_score = scores[0];
	int j;
	for (j = 1; j < scores.length; j++)
	    if (scores[j] > max_score)
		max_score = scores[j];
	boolean v[] = new boolean[scores.length];
	for (j = 0; j < scores.length; j++)
	    v[j] = (scores[j] == max_score);
	return new Label(v);
    }

    /**
     * Returns a preamble that would go at the beginning of C code
     * generated by a ComplexLearner.  The following must be defined
     * in the preamble:
     *    typedef Prediction_t  - the type of a prediction structure
     *                            in the C code
     *    #define reset_pred() - resets (zeros out) prediction p
     *    #define add_pred(b1,b2,...,br) - adds a prediction
     *                        represented by b1,...,br to p, where
     *                        b1,...,br would be returned by toCodeArray
     *    #define finalize_pred() - converts prediction p to
     *                        class scores, to be stored in the double
     *                        array r (unless r is NULL).  Returns
     *                        r[0] (or, if r is NULL, the value that
     *                        would have been computed for r[0] if r
     *                        were not NULL).
     */
    public abstract String cPreamble();

    /**
     * Returns code that would go inside Java code
     * generated by a ComplexLearner.  The following must be defined
     * in this code:
     *    p - a static private prediction object
     *    static private void reset_pred() - resets (zeros out) prediction p
     *    static private void add_pred(b1,b2,...,br) - adds a prediction
     *                        represented by b1,...,br to p, where
     *                        b1,...,br would be returned by toCodeArray
     *    static private double[] finalize_pred() - converts prediction p to
     *                        class scores, to be stored in the returned double
     *                        array.
     */
    public abstract String javaPreamble();

    /**
     * Converts to an array of doubles to be used by
     * add_pred macro defined in cPreamble.
     */
    public abstract double[] toCodeArray();

}