可视化具有连通性的聚类
通过用不同颜色绘制数据点来可视化具有连通性的聚类。
for n_clusters in (30, 3):
plt.figure(figsize=(10, 4))
for index, linkage in enumerate(("average", "complete", "ward", "single")):
plt.subplot(1, 4, index + 1)
model = AgglomerativeClustering(
linkage=linkage, connectivity=knn_graph, n_clusters=n_clusters
)
t0 = time.time()
model.fit(X)
elapsed_time = time.time() - t0
plt.scatter(X[:, 0], X[:, 1], c=model.labels_, cmap=plt.cm.nipy_spectral)
plt.title(
"linkage=%s\n(time %.2fs)" % (linkage, elapsed_time),
fontdict=dict(verticalalignment="top"),
)
plt.axis("equal")
plt.axis("off")
plt.subplots_adjust(bottom=0, top=0.83, wspace=0, left=0, right=1)
plt.suptitle(
"n_cluster=%i, connectivity=%r"
% (n_clusters, True),
size=17,
)
plt.show()