test(

function.py

@@ -39,7 +39,7 @@ name = "向兴宇"
 
 
 # 这里写自己的代码实现
-# import numba
+import numba
 
 
 # @numba.jit(nopython=True, fastmath=True)
@@ -68,10 +68,10 @@ 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(distances, k)[:k]])
+    classCount = np.bincount(labels[np.argpartition(np.einsum("ij,jk,ik->i", diff, _cache["VI"], diff), k)[:k]])
 
-    # 究极堆叠，减少赋值操作
-    return np.argmax(np.bincount(labels[np.argpartition(np.einsum("ij,jk,ik->i", diff, _cache["VI"], diff), k)[:k]]))
+    # 返回出现次数最多的标签
+    return np.argmax(classCount)
 
 
 def load_data(file_path):