| | |
- best_map(l1, l2)
- Permute labels of l2 to match l1 as much as possible
- evaluation(X_selected, n_clusters, y)
- This function calculates ARI, ACC and NMI of clustering results
Input
-----
X_selected: {numpy array}, shape (n_samples, n_selected_features}
input data on the selected features
n_clusters: {int}
number of clusters
y: {numpy array}, shape (n_samples,)
true labels
Output
------
nmi: {float}
Normalized Mutual Information
acc: {float}
Accuracy
|