I am working on a recommendation engine, and I have chosen to use SciPy's cosine distance as a way of comparing items.

I have two vectors:

a = [2.7654870801855078, 0.35995355443076027, 0.016221679989074141, -0.012664358453398751, 0.0036888812311235068]


b = [-6.2588482809118942, -0.88952297609194686, 0.017336984676103874, -0.0054928004763216964, 0.011122959185936367]

Running the following code will produce an output of ~1.999:

from scipy.spatial import distance

Is there something wrong with my input values? Anyone know why I am getting a result of >1?


1 Answer 1


The cosine distance formula is:

enter image description here

And the formula used by the cosine function of the spatial class of scipy is:

enter image description here

So, the actual cosine similarity metric is: -0.9998.

So, it signifies complete dissimilarity.


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