From: Topic modeling for cluster analysis of large biological and medical datasets
Methods | k | Cluster ID | Adenocarcinoma | Squamous cell carcinoma | No. of misclassified samples | NMI |
---|---|---|---|---|---|---|
Topic model-derived clustering based on feature selection | 2 | 1 | 42 | 11 | 22 | 0.2809 |
 |  | 2 | 11 | 47 |  |  |
 | 3 | 1 | 40 | 8 | 21 | 0.2417 |
 |  | 2 | 4 | 15 |  |  |
 |  | 3 | 9 | 35 |  |  |
 | 4 | 1 | 37 | 8 | 18 | 0.2926 |
 |  | 2 | 9 | 35 |  |  |
 |  | 3 | 0 | 14 |  |  |
 |  | 4 | 7 | 1 |  |  |
k-means | 2 | 1 | 41 | 12 | 24 | 0.2461 |
 |  | 2 | 12 | 46 |  |  |
 | 3 | 1 | 8 | 35 | 31 | 0.1365 |
 |  | 2 | 27 | 17 |  |  |
 |  | 3 | 18 | 6 |  |  |
 | 4 | 1 | 6 | 14 | 25 | 0.1602 |
 |  | 2 | 22 | 6 |  |  |
 |  | 3 | 18 | 6 |  |  |
 |  | 4 | 7 | 32 |  |  |
PCA (10 features) + k-means | 2 | 1 | 12 | 46 | 24 | 0.2461 |
 |  | 2 | 41 | 12 |  |  |
 | 3 | 1 | 8 | 35 | 31 | 0.1456 |
 |  | 2 | 22 | 6 |  |  |
 |  | 3 | 23 | 17 |  |  |
 | 4 | 1 | 16 | 5 | 25 | 0.1605 |
 |  | 2 | 6 | 14 |  |  |
 |  | 3 | 7 | 32 |  |  |
 |  | 4 | 24 | 7 |  |  |