更新 function.py

function.py

@@ -112,11 +112,15 @@ def load_data(filepath):
     X[X == '?'] = np.nan
 
     # 将特征数据转换为浮点数
-    X = X.astype(float)
+    try:
+        X = X.astype(float)
+    except ValueError as e:
+        print(f"转换特征数据时出错: {e}")
+        print("特征数据内容:", X)
 
     # 处理缺失值：可以选择填充或删除
     # 这里选择用列的均值填充缺失值
-    col_mean = np.nanmean(X, axis=0)  # 计算每列的均值
+    col_mean = np.nanmean(X.astype(float), axis=0)  # 计算每列的均值
     inds = np.where(np.isnan(X))  # 找到缺失值的索引
     X[inds] = np.take(col_mean, inds[1])  # 用均值填充缺失值