# mlclass / exercise-7 / octave / computeCentroids.m

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51``` ```function centroids = computeCentroids(X, idx, K) %COMPUTECENTROIDS returs the new centroids by computing the means of the %data points assigned to each centroid. % centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by % computing the means of the data points assigned to each centroid. It is % given a dataset X where each row is a single data point, a vector % idx of centroid assignments (i.e. each entry in range [1..K]) for each % example, and K, the number of centroids. You should return a matrix % centroids, where each row of centroids is the mean of the data points % assigned to it. % % Useful variables [m n] = size(X); % You need to return the following variables correctly. centroids = zeros(K, n); % ====================== YOUR CODE HERE ====================== % Instructions: Go over every centroid and compute mean of all points that % belong to it. Concretely, the row vector centroids(i, :) % should contain the mean of the data points assigned to % centroid i. % % Note: You can use a for-loop over the centroids to compute this. % agg = zeros(K,size(X,2)); cntr = zeros(K,1); for r=1:size(X,1) agg(idx(r),:) = agg(idx(r),:) + X(r,:); cntr(idx(r)) = cntr(idx(r)) + 1; end for r = 1:size(agg,1) centroids(r,:) = agg(r,:) / cntr(r); end % ============================================================= end ```