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Compute centroid means (unvectorized)

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neingeist 2014-11-17 23:02:10 +01:00
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ex7/computeCentroids.m
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@ -1,7 +1,7 @@
function centroids = computeCentroids(X, idx, K) function centroids = computeCentroids(X, idx, K)
%COMPUTECENTROIDS returs the new centroids by computing the means of the %COMPUTECENTROIDS returs the new centroids by computing the means of the
%data points assigned to each centroid. %data points assigned to each centroid.
% centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by % centroids = COMPUTECENTROIDS(X, idx, K) returns the new centroids by
% computing the means of the data points assigned to each centroid. It is % 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 % 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 % idx of centroid assignments (i.e. each entry in range [1..K]) for each
@ -19,18 +19,27 @@ centroids = zeros(K, n);
% ====================== YOUR CODE HERE ====================== % ====================== YOUR CODE HERE ======================
% Instructions: Go over every centroid and compute mean of all points that % Instructions: Go over every centroid and compute mean of all points that
% belong to it. Concretely, the row vector centroids(i, :) % belong to it. Concretely, the row vector centroids(k, :)
% should contain the mean of the data points assigned to % should contain the mean of the data points assigned to
% centroid i. % centroid k.
% %
% Note: You can use a for-loop over the centroids to compute this. % Note: You can use a for-loop over the centroids to compute this.
% %
for k = 1:K
count = 0;
% XXX vectorize
for i = 1:m
if idx(i) == k
centroids(k, :) += X(i, :);
count += 1;
end
end
if count > 0
centroids(k, :) /= count;
end
end
% ============================================================= % =============================================================