How to make Cosine Distance classification

10 Ansichten (letzte 30 Tage)
Kong
Kong am 12 Mär. 2020
Bearbeitet: Abbas Cheddad am 22 Mai 2024
Hello.
I have 90 dataset (10 label x 9 data).
I want to classfy the dataset using Cosine Distance.
How can use the below code to classify ?
function Cs = getCosineSimilarity(x,y)
%
% call:
%
% Cs = getCosineSimilarity(x,y)
%
% Compute Cosine Similarity between vectors x and y.
% x and y have to be of same length. The interpretation of
% cosine similarity is analogous to that of a Pearson Correlation
%
% R.G. Bettinardi
% -----------------------------------------------------------------
if isvector(x)==0 || isvector(y)==0
error('x and y have to be vectors!')
end
if length(x)~=length(y)
error('x and y have to be same length!')
end
xy = dot(x,y);
nx = norm(x);
ny = norm(y);
nxny = nx*ny;
Cs = xy/nxny;
  1 Kommentar
Abbas Cheddad
Abbas Cheddad am 22 Mai 2024
Bearbeitet: Abbas Cheddad am 22 Mai 2024
Cs = xy/nxny;
Should be written as:
Cs = 1 - xy/nx/ny;
This will give you the cosine distance.

Melden Sie sich an, um zu kommentieren.

Akzeptierte Antwort

Raunak Gupta
Raunak Gupta am 16 Mär. 2020
Hi,
I think the answer to the above question is provided in a similar question here. You may find it useful.

Weitere Antworten (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by