[BUG] Fix HIVE-COTE2 sporadic test failure (#3094)

* ensure at least 2 classes for CIT

* 2

sktime/classification/interval_based/_drcif.py

@@ -571,6 +571,11 @@ def _train_probas_for_estimator(self, y, idx):
 
         indices = range(self.n_instances_)
         subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
+        # subsample must have at least 2 unique classes
+        while len(np.unique(y[subsample])) == 1:
+            subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
         oob = [n for n in indices if n not in subsample]
 
         results = np.zeros((self.n_instances_, self.n_classes_))

sktime/classification/kernel_based/_arsenal.py

@@ -390,6 +390,11 @@ def _train_probas_for_estimator(self, y, idx):
 
         indices = range(self.n_instances_)
         subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
+        # subsample must have at least 2 unique classes
+        while len(np.unique(y[subsample])) == 1:
+            subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
         oob = [n for n in indices if n not in subsample]
 
         results = np.zeros((self.n_instances_, self.n_classes_))

sktime/classification/sklearn/_rotation_forest.py

@@ -451,6 +451,11 @@ def _train_probas_for_estimator(self, y, idx):
 
         indices = range(self.n_instances_)
         subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
+        # subsample must have at least 2 unique classes
+        while len(np.unique(y[subsample])) == 1:
+            subsample = rng.choice(self.n_instances_, size=self.n_instances_)
+
         oob = [n for n in indices if n not in subsample]
 
         results = np.zeros((self.n_instances_, self.n_classes_))