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Random initialization

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neingeist 2014-11-17 23:20:44 +01:00
parent 6c51a29ca2
commit 5f3f65c69c
2 changed files with 6 additions and 7 deletions
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1
ex7/ex7.m
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@ -86,6 +86,7 @@ max_iters = 10;
% settings them to be random examples (as can be seen in % settings them to be random examples (as can be seen in
% kMeansInitCentroids). % kMeansInitCentroids).
initial_centroids = [3 3; 6 2; 8 5]; initial_centroids = [3 3; 6 2; 8 5];
%initial_centroids = kMeansInitCentroids(X, K);
% Run K-Means algorithm. The 'true' at the end tells our function to plot % Run K-Means algorithm. The 'true' at the end tells our function to plot
% the progress of K-Means % the progress of K-Means

12
ex7/kMeansInitCentroids.m
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@ -1,5 +1,5 @@
function centroids = kMeansInitCentroids(X, K) function centroids = kMeansInitCentroids(X, K)
%KMEANSINITCENTROIDS This function initializes K centroids that are to be %KMEANSINITCENTROIDS This function initializes K centroids that are to be
%used in K-Means on the dataset X %used in K-Means on the dataset X
% centroids = KMEANSINITCENTROIDS(X, K) returns K initial centroids to be % centroids = KMEANSINITCENTROIDS(X, K) returns K initial centroids to be
% used with the K-Means on the dataset X % used with the K-Means on the dataset X
@ -13,12 +13,10 @@ centroids = zeros(K, size(X, 2));
% the dataset X % the dataset X
% %
% Randomly reorder the indices of examples
randidx = randperm(size(X, 1));
% Take the first K examples as centroids
centroids = X(randidx(1:K), :);
% ============================================================= % =============================================================