更新 function.py

function.py

@@ -39,23 +39,30 @@ name = "陈垣豪"
 - int: 预测的分类标签。
 """
 
-
-# 这里写自己的代码实现
 def classify0(inX, dataSet, labels, k=3):
-    distances = np.sqrt(np.sum((dataSet - inX) ** 2, axis=1))
+    # 计算协方差矩阵并求其逆矩阵
+    cov_matrix = np.cov(dataSet, rowvar=False)
+    inv_cov_matrix = np.linalg.inv(cov_matrix)
+    
+    # 计算马氏距离
+    diff = dataSet - inX
+    distances = np.sqrt(np.sum(diff @ inv_cov_matrix * diff, axis=1))
+    
     # 获取距离最小的 k 个样本的索引
     sorted_indices = np.argsort(distances)[:k] 
+    
     # 获取 k 个最近邻的标签
     nearest_labels = [labels[i] for i in sorted_indices]
-        # 统计 k 个最近邻中每个类别的出现次数
+    
+    # 统计 k 个最近邻中每个类别的出现次数
     label_count = {}
     for label in nearest_labels:
         if label in label_count:
             label_count[label] += 1
         else:
             label_count[label] = 1
+    
     # 找到出现次数最多的标签
     predicted_label = max(label_count, key=label_count.get)
-        
+    
     return predicted_label
-