Measure

The F-Measure is the harmonic mean of precision and recall, also known as the the traditional F-measure, balanced F-score, or F1-score: Formula: 2*Precision*Recall/(Precision+Recall) See: http://en.wikipedia.org/wiki/Precision_and_recall F-measure is defined only for a specific class value, and should thus be labeled with the class value for which is was computed. Use the mean_weighted_f_measure for the weighted average over all class values.

Source Code:

WEKA's Evaluation.fMeasure(int classIndex): /** * Calculate the F-Measure with respect to a particular class. * This is defined as*

* 2 * recall * precision * ---------------------- * recall + precision ** * @param classIndex the index of the class to consider as "positive" * @return the F-Measure */ public double fMeasure(int classIndex) { double precision = precision(classIndex); double recall = recall(classIndex); if ((precision + recall) == 0) { return 0; } return 2 * precision * recall / (precision + recall); }

Minimum value | 0 |

Maximum value | 0 |

Unit | |

Optimization | Higher is better |