diff --git a/docs/classification/core.md b/docs/classification/core.md
new file mode 100644
index 00000000..55ae57ea
--- /dev/null
+++ b/docs/classification/core.md
@@ -0,0 +1,3 @@
+## Classifications
+
+:::supervision.classification.core.Classifications
diff --git a/docs/dataset/core.md b/docs/dataset/core.md
index 0713c9dc..618f671b 100644
--- a/docs/dataset/core.md
+++ b/docs/dataset/core.md
@@ -5,4 +5,8 @@
 
 ## DetectionDataset
 
-:::supervision.dataset.core.DetectionDataset
\ No newline at end of file
+:::supervision.dataset.core.DetectionDataset
+
+## ClassificationDataset
+
+:::supervision.dataset.core.ClassificationDataset
\ No newline at end of file
diff --git a/supervision/.DS_Store b/supervision/.DS_Store
new file mode 100644
index 00000000..766f9f81
Binary files /dev/null and b/supervision/.DS_Store differ
diff --git a/supervision/__init__.py b/supervision/__init__.py
index b62c73c3..28bd6d8d 100644
--- a/supervision/__init__.py
+++ b/supervision/__init__.py
@@ -1,7 +1,11 @@
 __version__ = "0.9.0"
 
 from supervision.classification.core import Classifications
-from supervision.dataset.core import BaseDataset, DetectionDataset, ClassificationDataset
+from supervision.dataset.core import (
+    BaseDataset,
+    ClassificationDataset,
+    DetectionDataset,
+)
 from supervision.detection.annotate import BoxAnnotator, MaskAnnotator
 from supervision.detection.core import Detections
 from supervision.detection.line_counter import LineZone, LineZoneAnnotator
diff --git a/supervision/classification/.DS_Store b/supervision/classification/.DS_Store
new file mode 100644
index 00000000..08b4929c
Binary files /dev/null and b/supervision/classification/.DS_Store differ
diff --git a/supervision/dataset/core.py b/supervision/dataset/core.py
index d0564688..926672e8 100644
--- a/supervision/dataset/core.py
+++ b/supervision/dataset/core.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import os
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from pathlib import Path
@@ -8,9 +9,7 @@ from typing import Dict, Iterator, List, Optional, Tuple
 import cv2
 import numpy as np
 
-import os
 from supervision.classification.core import Classifications
-
 from supervision.dataset.formats.pascal_voc import (
     detections_to_pascal_voc,
     load_pascal_voc_annotations,
diff --git a/test/classification/__init__.py b/test/classification/__init__.py
new file mode 100644
index 00000000..e69de29b
diff --git a/test/classification/test_core.py b/test/classification/test_core.py
new file mode 100644
index 00000000..e742720d
--- /dev/null
+++ b/test/classification/test_core.py
@@ -0,0 +1,39 @@
+from typing import List, TypeVar, Optional, Tuple
+from contextlib import ExitStack as DoesNotRaise
+
+import pytest
+import numpy as np
+
+from supervision.classification.core import Classifications
+
+T = TypeVar("T")
+
+
+@pytest.mark.parametrize(
+    'class_id, confidence, expected_result, exception',
+    [
+        (
+            [0, 1, 2, 3, 4],
+            [0.1, 0.2, 0.9, 0.4, 0.5],
+            (np.array([2, 4, 3, 1, 0]), np.array([0.9, 0.5, 0.4, 0.2, 0.1])),
+            DoesNotRaise()
+        ),  # class_id with 5 numbers and 5 confidences
+        (
+            [0, 1, 2, 3, 4],
+            [0.1, 0.2, 0.3, 0.4],
+            None,
+            pytest.raises(ValueError)
+        ),  # class_id with 5 numbers and 4 confidences
+    ]
+)
+def test_top_k(
+    class_id: List[T],
+    confidence: Optional[List[T]],
+    expected_result: Optional[Tuple[List[T], List[T]]],
+    exception: Exception
+) -> None:
+    with exception:
+        result = Classifications(class_id=np.array(class_id), confidence=np.array(confidence)).get_top_k(len(class_id))
+
+        assert result[0].tolist() == expected_result[0].tolist()
+        assert result[1].tolist() == expected_result[1].tolist()