吴恩达的机器学习编程作业17：computeCentroids KMeans算法第二步计算质心

最新推荐文章于 2023-05-29 12:58:20 发布

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最新推荐文章于 2023-05-29 12:58:20 发布 · 1k 阅读

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本文深入探讨吴恩达机器学习课程中的KMeans算法，重点解析编程作业中计算质心的步骤。通过理解质心的计算方法，帮助读者更好地掌握聚类核心概念。

function centroids = computeCentroids(X, idx, K)
%COMPUTECENTROIDS returns 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, :)
%               sh