Module 1: Basics and Background
Lecture 3: Error Measures
Parameters for errors
Recall
or
Sensitivity
=
Proportion of answers found
Precision
=
Proportion of "true" answers in those found
Specificity
Proportion of" "true" non-answers in those not found
F-score
or
F-measure
=
Single measure capturing both precision and recall
Recall is
times more important than precision
When
=1, it is the harmonic mean of precision and recall
Accuracy
=
Proportion of objects correctly classified as answers and non-answers
ROC (Receiver Operating Characteristics) Curve
:
Sensitivity (y-axis) vs. 1 - Specificity (x-axis)