更新 function.py

function.py

@@ -1,5 +1,6 @@
 import numpy as np
 from sklearn.tree import DecisionTreeClassifier
+
 """
 实验说明:
 - 自行编写实现数据加载与预测病马死亡的对率回归算法。
@@ -16,8 +17,6 @@ from sklearn.tree import DecisionTreeClassifier
 id = "202210423208"
 name = "刘义天"
 
-
-
 # 加载数据并添加非线性特征
 def load_data(filepath):
     """
@@ -55,7 +54,6 @@ def load_data(filepath):
     
     return X, y
 
-
 # 对率回归训练函数
 def train_logreg(X, y, learning_rate=0.01, num_iterations=1000, regularization_strength=0):
     """
@@ -79,7 +77,6 @@ def train_logreg(X, y, learning_rate=0.01, num_iterations=1000, regularization_s
         weights -= learning_rate * gradient
     return weights
 
-
 # 决策树训练函数
 def train_decision_tree(X, y):
     """
@@ -96,7 +93,6 @@ def train_decision_tree(X, y):
     clf.fit(X, y)
     return clf
 
-
 # 对率回归预测函数
 def predict_logreg(inX, weights):
     """
@@ -112,7 +108,6 @@ def predict_logreg(inX, weights):
     probability = 1 / (1 + np.exp(-np.dot(inX, weights)))
     return 1 if probability >= 0.4 else 0
 
-
 # 融合预测函数
 def predict_fusion(inX, weights, clf):
     """