feat: add cal_external_cluster_validation_metrics();

pypots/utils/metrics.py

@@ -599,6 +599,37 @@ def cal_cluster_purity(
  return cluster_purity
 
 
+def cal_external_cluster_validation_metrics(class_predictions, targets):
+ """Computer all external cluster validation metrics available in PyPOTS and return as a dictionary.
+
+ Parameters
+ ----------
+ class_predictions :
+ Clustering results returned by a clusterer.
+
+ targets :
+ Ground truth (correct) clustering results.
+
+ Returns
+ -------
+ external_cluster_validation_metrics : dict
+ A dictionary contains all external cluster validation metrics available in PyPOTS.
+ """
+
+ ri = cal_rand_index(class_predictions, targets)
+ ari = cal_adjusted_rand_index(class_predictions, targets)
+ nmi = cal_nmi(class_predictions, targets)
+ cp = cal_cluster_purity(class_predictions, targets)
+
+ external_cluster_validation_metrics = {
+ "rand_index": ri,
+ "adjusted_rand_index": ari,
+ "nmi": nmi,
+ "cluster_purity": cp,
+ }
+ return external_cluster_validation_metrics
+
+
 def cal_silhouette(X: np.ndarray, predicted_labels: np.ndarray) -> float:
  """Compute the mean Silhouette Coefficient of all samples.