Similarity Measure – IOU – (Jaccard index)

Similarity Measure

The Jaccard index/coefficient, aka Intersection over Union is used  in computer vision as one of the similarity measures for object detection on images.

Formula

The Jaccard similarity coefficient,aka Intersection over Union (IOU) score:

 

 

Binary classification  Formula

The same score above can be described as binary classification as well to get an ML algorithm to use it:

And can also be noted in writing as:

true positive / (true positive + false positive + false negative)

  • M11 is always the intersection- aka true positive
  • M01 is the false positive
  • M10 is the false negative
  • M00 is not used in the formula as it is the complement

Code Example in R

 Calc_Jaccard_Index <- function(vector1, vector2){
         Jaccard_Index<(sum(which(vector1==1)%in%which(vector2==1)) /
                       (sum(which(vector1==0)%in%which(vector2==1)) +
                       sum(which(vector1==1)%in%which(vector2==0)) +
                       sum(which(vector1==1)%in%which(vector2==1))))
        return(Jaccard_Index)
}

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