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ResearchFormerly WizWand

Clustering on Uniform Distribution R^d (test)

0Runtime (s)K-Means
-0.32161.84924.026.1908Apr 8, 2026
Updated 6mo ago

Evaluation results

MethodLinks
K-Meansinit=k-means++, d=2, k=2, n=10,0002026.040
K-Meansinit=k-means++, d=5, k=2, n=10,0002026.040
LumbermarkM=1, d=2, k=2, n=10,0002026.040.01
LumbermarkM=10, d=2, k=2, n=10,0002026.040.01
LumbermarkM=1, d=2, k=10, n=10,0002026.040.01
LumbermarkM=10, d=2, k=10, n=10,0002026.040.01
K-Meansinit=k-means++, d=2, k=10, n=10,0002026.040.01
K-Meansinit=k-means++, d=10, k=2, n=10,0002026.040.01
K-Meansinit=random, d=2, k=2, n=10,0002026.040.02
EM for Gaussian mixturesd=2, k=2, n=10,0002026.040.02
K-Meansinit=k-means++, d=2, k=2, n=100,0002026.040.02
LumbermarkM=1, d=5, k=2, n=10,0002026.040.02
LumbermarkM=10, d=5, k=2, n=10,0002026.040.02
EM for Gaussian mixturesd=5, k=2, n=10,0002026.040.02
LumbermarkM=1, d=5, k=10, n=10,0002026.040.02
LumbermarkM=10, d=5, k=10, n=10,0002026.040.02
K-Meansinit=k-means++, d=5, k=10, n=10,0002026.040.02
K-Meansinit=k-means++, d=10, k=10, n=10,0002026.040.02
K-Meansinit=random, d=5, k=2, n=10,0002026.040.03
K-Meansinit=k-means++, d=5, k=2, n=100,0002026.040.03
K-Meansinit=random, d=10, k=2, n=10,0002026.040.03
EM for Gaussian mixturesd=10, k=2, n=10,0002026.040.03
K-Meansinit=k-means++, d=10, k=2, n=100,0002026.040.03
K-Meansinit=random, d=2, k=10, n=10,0002026.040.04
HDBSCANvariant=fast, d=2, k=2, n=10,0002026.040.05
EM for Gaussian mixturesd=2, k=10, n=10,0002026.040.05
K-Meansinit=k-means++, d=2, k=10, n=100,0002026.040.05
HDBSCANvariant=fast, d=5, k=2, n=10,0002026.040.06
LumbermarkM=1, d=2, k=2, n=100,0002026.040.07
LumbermarkM=10, d=2, k=2, n=100,0002026.040.09
K-Meansinit=random, d=2, k=2, n=100,0002026.040.09
K-Meansinit=random, d=5, k=10, n=10,0002026.040.09
LumbermarkM=1, d=10, k=2, n=10,0002026.040.09
LumbermarkM=10, d=10, k=2, n=10,0002026.040.09
LumbermarkM=1, d=10, k=10, n=10,0002026.040.09
LumbermarkM=10, d=10, k=10, n=10,0002026.040.09
LumbermarkM=1, d=2, k=10, n=100,0002026.040.1
LumbermarkM=10, d=2, k=10, n=100,0002026.040.11
EM for Gaussian mixturesd=2, k=2, n=100,0002026.040.12
K-Meansinit=random, d=5, k=2, n=100,0002026.040.12
K-Meansinit=k-means++, d=5, k=10, n=100,0002026.040.12
K-Meansinit=random, d=10, k=2, n=100,0002026.040.12
HDBSCANvariant=std, d=2, k=2, n=10,000, allows_requesting_k=false2026.040.15
K-Meansinit=random, d=10, k=10, n=10,0002026.040.15
K-Meansinit=k-means++, d=2, k=2, n=1,000,0002026.040.16
LumbermarkM=1, d=5, k=2, n=100,0002026.040.16
K-Meansinit=k-means++, d=10, k=10, n=100,0002026.040.18
EM for Gaussian mixturesd=5, k=2, n=100,0002026.040.19
K-Meansinit=random, d=2, k=10, n=100,0002026.040.2
LumbermarkM=1, d=5, k=10, n=100,0002026.040.2
LumbermarkM=10, d=5, k=2, n=100,0002026.040.21
K-Meansinit=k-means++, d=5, k=2, n=1,000,0002026.040.21
EM for Gaussian mixturesd=10, k=2, n=100,0002026.040.21
LumbermarkM=10, d=5, k=10, n=100,0002026.040.23
HDBSCANvariant=fast, d=10, k=2, n=10,0002026.040.23
EM for Gaussian mixturesd=5, k=10, n=10,0002026.040.24
K-Meansinit=k-means++, d=10, k=2, n=1,000,0002026.040.32
HDBSCANvariant=std, d=5, k=2, n=10,000, allows_requesting_k=false2026.040.44
K-Meansinit=random, d=5, k=10, n=100,0002026.040.46
K-Meansinit=k-means++, d=2, k=10, n=1,000,0002026.040.51
K-Meansinit=random, d=2, k=2, n=1,000,0002026.040.59
HDBSCANvariant=fast, d=2, k=2, n=100,0002026.040.66
EM for Gaussian mixturesd=2, k=10, n=100,0002026.040.69
EM for Gaussian mixturesd=10, k=10, n=10,0002026.040.76
HDBSCANvariant=fast, d=5, k=2, n=100,0002026.040.84
K-Meansinit=k-means++, d=5, k=10, n=1,000,0002026.040.95
K-Meansinit=random, d=5, k=2, n=1,000,0002026.040.99
EM for Gaussian mixturesd=2, k=2, n=1,000,0002026.041.04
LumbermarkM=1, d=2, k=2, n=1,000,0002026.041.23
HDBSCANvariant=std, d=10, k=2, n=10,000, allows_requesting_k=false2026.041.26
LumbermarkM=10, d=2, k=2, n=1,000,0002026.041.33
K-Meansinit=random, d=10, k=10, n=100,0002026.041.35
Ward linkaged=2, k=10, n=10,0002026.041.36
Ward linkaged=2, k=2, n=10,0002026.041.37
K-Meansinit=k-means++, d=10, k=10, n=1,000,0002026.041.38
EM for Gaussian mixturesd=5, k=2, n=1,000,0002026.041.41
LumbermarkM=1, d=10, k=2, n=100,0002026.041.45
LumbermarkM=1, d=10, k=10, n=100,0002026.041.49
Ward linkaged=5, k=2, n=10,0002026.041.56
Ward linkaged=5, k=10, n=10,0002026.041.57
LumbermarkM=10, d=10, k=2, n=100,0002026.041.58
LumbermarkM=10, d=10, k=10, n=100,0002026.041.6
K-Meansinit=random, d=10, k=2, n=1,000,0002026.041.7
Ward linkaged=10, k=2, n=10,0002026.041.72
Ward linkaged=10, k=10, n=10,0002026.041.73
K-Meansinit=random, d=2, k=10, n=1,000,0002026.041.9
EM for Gaussian mixturesd=10, k=2, n=1,000,0002026.042.14
LumbermarkM=10, d=2, k=10, n=1,000,0002026.042.15
LumbermarkM=1, d=5, k=2, n=1,000,0002026.042.22
HDBSCANvariant=std, d=2, k=2, n=100,000, allows_requesting_k=false2026.042.27
LumbermarkM=1, d=2, k=10, n=1,000,0002026.042.37
LumbermarkM=10, d=5, k=2, n=1,000,0002026.042.63
LumbermarkM=10, d=5, k=10, n=1,000,0002026.043.54
LumbermarkM=1, d=5, k=10, n=1,000,0002026.043.64
HDBSCANvariant=fast, d=10, k=2, n=100,0002026.044
EM for Gaussian mixturesd=5, k=10, n=100,0002026.045.4
K-Meansinit=random, d=5, k=10, n=1,000,0002026.046.18
EM for Gaussian mixturesd=2, k=10, n=1,000,0002026.046.24
EM for Gaussian mixturesd=10, k=10, n=100,0002026.046.86
HDBSCANvariant=std, d=5, k=2, n=100,000, allows_requesting_k=false2026.048.04