更新 function.py

function.py

@@ -27,17 +27,10 @@ def classify(input_vector, dataSet, labels, k=3):
     # 获取距离最近的 k 个样本的索引
     sortedDistIndices = distances.argsort()
     classCount = {}
-    weightSum = {}
-    # 使用加权多数表决法
     for i in range(k):
         voteIlabel = labels[sortedDistIndices[i]]
-        # 统计每个类别的出现次数，并使用距离的倒数作为权重
-        weight = 1 / (distances[sortedDistIndices[i]] + 1e-5)  # 加上一个小常数防止除以零
-        classCount[voteIlabel] = classCount.get(voteIlabel, 0) + weight
-        weightSum[voteIlabel] = weightSum.get(voteIlabel, 0) + 1
-    # 计算加权平均值
-    for className in classCount:
-        classCount[className] /= weightSum[className]
+        # 统计每个类别的出现次数
+        classCount[voteIlabel] = classCount.get(voteIlabel, 0) + 1
     # 返回出现次数最多的类别
     sortedClassCount = sorted(classCount.items(), key=lambda x: x[1], reverse=True)
     return sortedClassCount[0][0]