更新 function.py

function.py

@@ -25,8 +25,15 @@ id = "202210423204"
 name = "陈垣豪"
 
 
-import numpy as np
-from sklearn.preprocessing import StandardScaler
+def load_data(filepath):
+    """加载数据并处理缺失值."""
+    data = np.genfromtxt(filepath, delimiter=' ', dtype=float, missing_values='?', filling_values=np.nan)
+    nan_columns = np.isnan(data)
+    mean_values = np.nanmean(data, axis=0)
+    data[nan_columns] = np.take(mean_values, np.where(nan_columns)[1])
+    X = data[:, :-1]
+    y = data[:, -1]
+    return X, y
 
 def train_logreg(X, y, learning_rate=0.01, iterations=1000):
     """训练逻辑回归模型，使用随机梯度下降."""
@@ -49,17 +56,7 @@ def predict_logreg(inX, weights):
     """使用线性模型预测结果."""
     inX = np.append(inX, 1)  # 增加偏置项
     linear_model = np.dot(inX, weights)
-    return 1 if linear_model >= 0 else 0  # 直接返回0或1
-
-def load_data(filepath):
-    """加载数据并处理缺失值."""
-    data = np.genfromtxt(filepath, delimiter=' ', dtype=float, missing_values='?', filling_values=np.nan)
-    nan_columns = np.isnan(data)
-    mean_values = np.nanmean(data, axis=0)
-    data[nan_columns] = np.take(mean_values, np.where(nan_columns)[1])
-    X = data[:, :-1]
-    y = data[:, -1]
-    return X, y
+    return 1.0 if linear_model >= 0 else 2.0 
 
 if __name__ == "__main__":
     # 加载训练集