High-Dimensional Text Clustering by Dimensionality Reduction and Improved Density Peak

Table 4

The clustering performances of local density calculated by Euclidean distance and cosine similarity.

Dataset	ARI		NMI		FMI		Clusters
	Euclidean	Cosine	Euclidean	Cosine	Euclidean	Cosine	Euclidean	Cosine
BBC	0.8422	0.9002	0.8223	0.8681	0.8759	0.9204	5	5
4 groups	0.9715	0.9781	0.9523	0.9623	0.9786	0.9836	4	4
5 groups	0.8438	0.8433	0.8411	0.8381	0.8851	0.8846	5	5
6 groups	0.6195	0.6759	0.6874	0.7351	0.7326	0.7700	6	6
7 groups	0.2213	0.5858	0.3039	0.6487	0.4999	0.7031	5	7
8 groups	0.1889	0.4664	0.2672	0.5507	0.4607	0.6138	5	8
Sports Article	0	0	0	0	0.5674	0.7298	1	2
Asian Religious	0.0562	0.0189	0.1288	0.0163	0.3145	0.4665	6	8
Stack Overflow	0	0	0	0	0.3660	0.4399	2	4
Amazon	0	0.0014	0	0.0048	0.5515	0.6696	2	2
CNAE-9	—	—	—	—	—	—	6	9