更新 function.py

function.py

@@ -31,22 +31,36 @@ name = "董秋"
 def load_data(filepath):
     data = []
     labels = []
+    
     with open(filepath, 'r') as file:
         for line in file:
             fields = line.strip().split()
-            fields = [0 if f == '?' else float(f) for f in fields]  # 缺失值填充
+            
+            # 处理缺失值，用0填充
+            fields = [0 if f == '?' else float(f) for f in fields]  
+            
+            # 特征是除最后一列外的所有列
             features = np.array(fields[:-1], dtype=float)
+            
+            # 标签是最后一列
             label = int(fields[-1])
+            
+            # 添加数据和标签
             data.append(features)
             labels.append(label)
-    labels = np.array(labels)
     
-    # 检查标签是否为三类
+    # 转换为numpy数组
+    labels = np.array(labels)
+    data = np.array(data)
+
+    # 检查标签的唯一值，确保只有 0, 1, 2
     unique_labels = np.unique(labels)
+    
     if len(unique_labels) != 3:
+        print(f"错误：标签数据包含的类别不是3个，实际类别为：{unique_labels}")
         raise ValueError("标签数量不为3，请确保标签未合并！")
 
-    return np.array(data), labels
+    return data, labels
 
 def train_svm(X, y, learning_rate=0.01, iterations=1000, regularization_strength=0.01):
     n_samples, n_features = X.shape