Question

如何将具有相同箱数（8）但长度不同的大型直方图数据集聚类？具体来说，我想对它们的密度分布进行聚类。我认为我可以使用kmeans或分层集群来做到这一点，但似乎长度是一个问题，或者我的设置导致了ValueError: setting an array element with a sequence.

hist_data[:, 1]
array([
   array([3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 6,
   6, 6, 6, 6, 6, 6, 5, 4, 3, 3, 3, 3, 3, 3, 4, 5, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 5, 5, 5,
   5], dtype=int64),
   ...,
   array([6, 6, 6, 6, 6, 6, 6, 5, 5, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,
   3, 4, 4, 5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 6, 6, 5, 5, 4, 4, 3, 3, 3, 3, 3, 3, 3, 3, 3,
   3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 5, 5, 6, 6, 6, 6, 6, 6,
   6, 6, 6, 6, 6, 6, 6, 5, 5, 4, 4, 3, 3, 3, 3, 4, 5, 6, 6, 6, 6, 6,
   6, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
   5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,
   5, 5], dtype=int64)], dtype=object)

Answer 1

这符合要求吗？

import numpy as np
from sklearn.cluster import KMeans

data = hist_data[:, 1]
data = np.array([np.bincount(datum, minlength=9) for datum in data])
km = KMeans(n_clusters = 10, init="k-means++").fit(data)  # 10 clusters
print(km.cluster_centers_)  # cluster centres, 10x8 array

在Python中聚类不同长度的直方图

1 个答案: