I was studying Cosine Similarity and I have just seen this article. https://medium.com/@rahulkuntala9/cosine-similarity-and-handling-categorical-variables-29f907951b5
The author uses Cosine Similarity in order to find the similarity between the p1 and the other vectors.
p1 = (1,0,0,150), newp1 = (1,0,0,100), newp2 = (1,0,0,200), newp3 = (0,0,1,135) and newp4 = (0,1,0,250)
Similarity(p1,newp1) = 0.999994
Similarity(p1,newp2) = 0.999998
Similarity(p1,newp3) = 0.99995
Similarity(p1,newp4) = 0.99994
My question is: Since I want the Cosine Similarity to be the weight to some values, how can I use these results in order to do that? All the similarities are almost 1 with no actual differences. I think that there is no reason to use these results. I have thought to use Euclidean Distance to find the similarity but I know that it is not the best method to find similarity.
What do you propose? Thank you!