更新 function.py

function.py

@@ -55,19 +55,10 @@ def predict_logreg(inX, weights):
 # 从文件中加载数据  
 def load_data(filepath):
     data = pd.read_csv(filepath, header=None, na_values='?', delim_whitespace=True)
-
-    # 使用SimpleImputer进行中位数填充
-    imputer = SimpleImputer(strategy='median')
-    data_imputed = imputer.fit_transform(data)
-    data = pd.DataFrame(data_imputed)
-
+    data.fillna(0, inplace=True)
     X = data.iloc[:, :-1].to_numpy()  # 特征
     y = data.iloc[:, -1].to_numpy()    # 标签
-    # 使用MinMaxScaler进行特征缩放
-    scaler = MinMaxScaler()
-    X = scaler.fit_transform(X)
-    return X, y
-    
+    return X, y 
 # 准确率计算函数
 def calculate_accuracy(X, y, weights):
     predictions = np.array([predict_logreg(x, weights) for x in X])