Sphinx Docstring Update - Nearest Centroid

verticapy/machine_learning/memmodel/cluster.py

@@ -69,7 +69,7 @@ def __init__(
         clusters_names: Optional[ArrayLike] = None,
     ) -> None:
         clusters_names = format_type(clusters_names, dtype=list)
-        self.clusters_ = np.array(clusters)
+        self.clusters_ = np.array(clusters).astype(float)
         self.classes_ = np.array(clusters_names)
         self.p_ = p
 
@@ -380,7 +380,7 @@ def object_type(self) -> Literal["KMeans"]:
     # System & Special Methods.
 
     def __init__(self, clusters: ArrayLike, p: int = 2) -> None:
-        self.clusters_ = np.array(clusters)
+        self.clusters_ = np.array(clusters).astype(float)
         self.p_ = p
 
 
@@ -518,7 +518,7 @@ def __init__(
         classes: ArrayLike,
         p: int = 2,
     ) -> None:
-        self.clusters_ = np.array(clusters)
+        self.clusters_ = np.array(clusters).astype(float)
         self.classes_ = np.array(classes)
         self.p_ = p
 
@@ -720,7 +720,7 @@ def __init__(
         cluster_size, cluster_score = format_type(
             cluster_size, cluster_score, dtype=list
         )
-        self.clusters_ = np.array(clusters)
+        self.clusters_ = np.array(clusters).astype(float)
         self.children_left_ = np.array(children_left)
         self.children_right_ = np.array(children_right)
         self.cluster_size_ = np.array(cluster_size)

verticapy/machine_learning/metrics/classification.py

@@ -229,7 +229,7 @@ def _compute_final_score(
             "Parameter 'pos_label' can only be used when parameter 'average' is set to 'binary' or undefined."
         )
     if not (isinstance(pos_label, NoneType)) and not (isinstance(labels, NoneType)):
-        raise ValueError("Parameters 'pos_label' and 'labels' can not be both defined.")
+        labels = None
     if (
         isinstance(pos_label, NoneType)
         and isinstance(labels, NoneType)

verticapy/machine_learning/vertica/base.py

@@ -2215,7 +2215,7 @@ def score(
         kwargs = {}
         if metric not in ("aic", "bic"):
             labels = None
-            if isinstance(pos_label, NoneType):
+            if isinstance(pos_label, NoneType) or not (self._is_native):
                 labels = self.classes_
             kwargs = {
                 "average": average,