Table 2 Effectiveness of clustering of MDDR dataset using F-Measure: ALOGP Fingerprint
From: Voting-based consensus clustering for combining multiple clusterings of chemical structures
| Clustering method | No. of clusters | |||||||
|---|---|---|---|---|---|---|---|---|
| 500 | 600 | 700 | 800 | 900 | 1000 | |||
| Consensus clustering | CVAA | Correlation | 26.80 | 21.96 | 18.96 | 18.49 | 17.6 | 15.45 |
| Cosine | 24.79 | 21.72 | 19.01 | 18.19 | 16.46 | 14.81 | ||
| Euclidean | 27.96 | 23.75 | 22.68 | 24.30 | 21.17 | 19.95 | ||
| Hamming | 24.02 | 20.48 | 16.31 | 16.85 | 14.95 | 14.68 | ||
| Jaccard | 23.58 | 21.96 | 18.01 | 18.46 | 16.72 | 15.35 | ||
| Manhattan | 27.03 | 25.23 | 21.16 | 20.36 | 19.10 | 19.05 | ||
| CSPA | Correlation | 5.06 | 4.65 | 4.16 | 3.56 | 3.35 | 3.04 | |
| Cosine | 5.17 | 4.65 | 4.08 | 3.62 | 3.37 | 3.05 | ||
| Euclidean | 5.12 | 4.64 | 4.04 | 3.61 | 3.38 | 3.00 | ||
| Hamming | 5.30 | 4.74 | 4.16 | 3.62 | 3.54 | 3.13 | ||
| Jaccard | 5.31 | 4.82 | 4.15 | 3.77 | 3.48 | 3.13 | ||
| Manhattan | 5.33 | 4.80 | 4.21 | 3.62 | 3.45 | 3.05 | ||
| HGPA | Correlation | 7.13 | 5.48 | 5.45 | 4.65 | 4.35 | 4.37 | |
| Cosine | 8.06 | 6.04 | 5.03 | 4.52 | 4.45 | 4.08 | ||
| Euclidean | 7.08 | 6.55 | 5.65 | 4.67 | 4.56 | 4.60 | ||
| Hamming | 8.37 | 5.73 | 4.94 | 5.29 | 4.97 | 4.93 | ||
| Jaccard | 7.63 | 6.22 | 5.98 | 4.53 | 5.24 | 3.92 | ||
| Manhattan | 7.72 | 6.48 | 5.23 | 5.35 | 4.90 | 4.12 | ||
| Individual clustering | Ward's method | 9.93 | 9.19 | 8.19 | 7.17 | 6.67 | 6.44 | |