如何在 python 中获得 dbscan 创建的聚类的置信度

Question

我在python中使用了sklearn.dbscan，结果只给出了每个簇的标签，但我还想计算聚类的置信度，或者只是簇之间的平均距离.

你们有什么想法吗？

Answer 1

我认为 Scikit 不支持此功能。群集置信度不是问题，因为 DBSCAN 不使用群集概率。但是，计算簇距离相对简单。

import numpy as np
from sklearn.datasets import load_iris
from sklearn.cluster import dbscan


# Get data & labels
data = load_iris()['data']
labels = dbscan(data)[1]

import numpy as np
from sklearn.datasets import load_iris
from sklearn.cluster import dbscan


# Get data & labels
data = load_iris()['data']
labels = dbscan(data)[1]

# Initialize results
cluster_means = np.zeros((len(set(labels)) - 1, data.shape[1]))
cluster_distances = np.zeros((len(data), len(set(labels)) - 1))

# Loop through clusters
for i, cluster in enumerate(set(labels)):
    # Skip noise
    if cluster == -1:
        continue

    # Get cluster mean
    cluster_mean = np.mean(data[labels == cluster], axis=0)

    # Set cluster mean
    cluster_means[i, :] = cluster_mean

    # Set cluster distances
    cluster_distances[:, i] = np.linalg.norm(data - cluster_mean, axis=1)

如何在 python 中获得 dbscan 创建的聚类的置信度

how to get the confidence of clustering created by dbscan in python

python

cluster-analysis

dbscan