更新 function.py

function.py

@@ -25,8 +25,8 @@ import numpy as np
 """
 请在这里填写学号和姓名，不填写即成绩无效。
 """
-id = "202210423xxx"
+id = "202210423213"
-name = "test_name"
+name = "熊浩燃"
 
 
 """
@@ -54,7 +54,19 @@ def classify0(inX, dataSet, labels, k=0):
     Returns:
     - int: 预测的分类标签。
     """
+# 计算距离
+    distances = np.linalg.norm(dataSet - inX, axis=1)
     
+    # 获取距离最小的 k 个样本的索引
+    k_indices = np.argsort(distances)[:k]
+    
+    # 获取这 k 个样本的标签
+    k_nearest_labels = [labels[i] for i in k_indices]
+    
+    # 进行投票
+    most_common = np.bincount(k_nearest_labels).argmax()
+    
+    return most_common
 
 def load_data(file_path):
     """
@@ -70,7 +82,9 @@ if __name__ == "__main__":
     # 以下代码可用于测试，可自行随意修改
 
     train_file = "datingTrainSet2.tsv"
-
     train_data, train_labels = load_data(train_file)
     
-    print(classify0([65915, 3.868359, 0.128078], train_data, train_labels))
+    # 测试分类
+    sample = np.array([65915, 3.868359, 0.128078])
+    predicted_label = classify0(sample, train_data, train_labels)
+    print(f"Predicted label: {predicted_label}")