Could you re-try similar experiments on a semi-structured dataset (e.g. wide blob-ish clusters + uniform noise background) with a random train-test split and evaluate the impact of n_init on the SSE measured on the test data for the clusters returned by k-means++ for different n_init ...
n_clusters=8, # 聚类数量 init='k-means++', # 初始化质心的方法 n_init=10, # KMeans 算法重新运行的次数(初始质心选择不同) max_iter=300, # 最大迭代次数 tol=0.0001, # 容忍度,控制收敛的阈值 verbose=0, # 控制输出日志的详细程度 random_state=None, # 随机种子控制聚类的随机性 copy_x=Tru...
In the example: Empirical evaluation of the impact of k-means initialization, it does show that n_init > 1 leads to an improvement for init="random". For k-means++, n_init does not make a difference. If we go by the example, then we can have a n_init="auto", where: n_init=1...
init() got an unexpected keyword argument 'n_jobs'",我们可以从以下几个方面进行解答: 理解错误消息: 该错误消息表明,在初始化 kmeans 对象时,提供了一个不被 __init__ 方法接受的关键字参数 n_jobs。这通常意味着 n_jobs 参数在当前的 KMeans 类定义中不存在。 检查KMeans类的初始化方法__init__的...
n_init=10, max_iter=300, tol=1e-4, precompute_distances='deprecated', verbose=0, random_state=None, copy_x=True, n_jobs='deprecated', algorithm='auto'): self.n_clusters = n_clusters self.init = init self.max_iter = max_iter ...
initial_centroids = kMeansInitCentroids(X, K); [centroids, idx] = runkMeans(X, initial_centroids, max_iters); %开始压缩图片 idx = findClosestCentroids(X, centroids); X_recovered = centroids(idx,:); X_recovered = reshape(X_recovered, img_size(1), img_size(2), 3); ...
参数n_init到底有什么作用?我真的不明白。Moh*_*hif 5 在K-means中,质心的初始放置对其收敛起着非常重要的作用。有时,初始质心的放置方式使得在 K 均值的连续迭代期间,簇不断发生剧烈变化,甚至在收敛条件可能发生之前就max_iter达到了,我们留下了不正确的簇。因此,这样获得的聚类可能不正确。为了解决这个问题...
n_clusters:整型,缺省值=8 ,生成的聚类数。 max_iter:整型,缺省值=300 。 执行一次k-means算法所进行的最大迭代数。 n_init:整型,缺省值=10 。 用不同的聚类中心初始化值运行算法的次数,最终解是在inertia意义下选出的最优结果。 init:有三个可选值:’k-means++’, ‘random’,或者传递一个ndarray向量...
这样，您的quotient变量现在是 * 一个 * 样本;这里我得到了一个不同的错误消息，可能是由于不同的...
Setting n_jobs > 1 shouldn't do anything but makes things slower consistently.👎 1 dzad commented Mar 8, 2018 how large is your data? Member Author amueller commented Apr 6, 2018 Across several synthetic datasets. Member rth commented Jun 21, 2019 This will likely be resolved by ...