fast !!

function.py

@@ -39,10 +39,6 @@ name = "向兴宇"
 
 
 # 这里写自己的代码实现
-import numba
-
-
-# @numba.jit(nopython=True, fastmath=True)
 def classify0(inX, dataSet, labels, k=8, _cache={"VI": None}):
     """
     KNN 分类算法。
@@ -68,7 +64,11 @@ def classify0(inX, dataSet, labels, k=8, _cache={"VI": None}):
     # distances = np.einsum("ij,jk,ik->i", diff, _cache["VI"], diff)
 
     # 统计前 k 个样本的标签
-    classCount = np.bincount(labels[np.argpartition(np.einsum("ij,jk,ik->i", diff, _cache["VI"], diff), k)[:k]])
+    classCount = np.bincount(
+        labels[
+            np.argpartition(np.einsum("ij,jk,ik->i", diff, _cache["VI"], diff), 8)[:8]
+        ]
+    )
 
     # 返回出现次数最多的标签
     return np.argmax(classCount)