diff --git a/function.py b/function.py
index 2ee7ccf..5b38298 100644
--- a/function.py
+++ b/function.py
@@ -1,7 +1,5 @@
 # function.py
-pip install sklearn
-import numpy as np 
-from sklearn.preprocessing import StandardScaler  
+import numpy as np   
 from numpy.linalg import inv
 """
 挑战说明:
@@ -58,11 +56,7 @@ def classify0(inX, dataSet, labels, k=4, cov_inv=None):
     if cov_inv is None:  
         # 计算训练数据的协方差矩阵并求逆  
         cov_matrix = np.cov(dataSet.T)  
-        cov_inv = inv(cov_matrix)  
-  
-    # 计算待分类样本与所有训练样本之间的马氏距离  
-    # 注意：这里我们假设 inX 已经被适当地预处理（例如，通过 StandardScaler 归一化）  
-    # 并且 dataSet 也是用相同的预处理步骤处理的  
+        cov_inv = inv(cov_matrix)    
     differences = dataSet - inX  
     mahalanobis_distances = np.sqrt(np.sum(differences @ cov_inv @ differences.T, axis=1))