Package smile.validation.metric
Class FScore
java.lang.Object
smile.validation.metric.FScore
 All Implemented Interfaces:
Serializable
,ClassificationMetric
The Fscore (or Fmeasure) considers both the precision and the recall of the test
to compute the score. The precision p is the number of correct positive results
divided by the number of all positive results, and the recall r is the number of
correct positive results divided by the number of positive results that should
have been returned.
The traditional or balanced Fscore (F1 score) is the harmonic mean of precision and recall, where an F1 score reaches its best value at 1 and worst at 0.
The general formula involves a positive real β so that Fscore measures the effectiveness of retrieval with respect to a user who attaches β times as much importance to recall as precision.
 See Also:

Field Summary

Constructor Summary

Method Summary

Field Details

F1
The F_1 score, the harmonic mean of precision and recall. 
F2
The F_2 score, which weighs recall higher than precision. 
FHalf
The F_0.5 score, which weighs recall lower than precision.


Constructor Details

FScore
public FScore()Constructor of F1 score. 
FScore
public FScore(double beta) Constructor of general Fscore. Parameters:
beta
 a positive value such that Fscore measures the effectiveness of retrieval with respect to a user who attaches β times as much importance to recall as precision.


Method Details

score
public double score(int[] truth, int[] prediction) Description copied from interface:ClassificationMetric
Returns a score to measure the quality of classification. Specified by:
score
in interfaceClassificationMetric
 Parameters:
truth
 the true class labels.prediction
 the predicted class labels. Returns:
 the metric.

of
public static double of(double beta, int[] truth, int[] prediction) Calculates the F1 score. Parameters:
beta
 a positive value such that Fscore measures the effectiveness of retrieval with respect to a user who attaches β times as much importance to recall as precision.truth
 the ground truth.prediction
 the prediction. Returns:
 the metric.

toString
