From 3a1b0746a2e2a8ec987d17cc9d096817c6401c3e Mon Sep 17 00:00:00 2001
From: mogu-king <1547976000@qq.com>
Date: Sun, 3 Nov 2024 04:39:55 +0800
Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20function.py?=
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---
 function.py | 20 ++++++++++++++++++--
 1 file changed, 18 insertions(+), 2 deletions(-)

diff --git a/function.py b/function.py
index 8182d90..1d98e5c 100644
--- a/function.py
+++ b/function.py
@@ -17,6 +17,7 @@ id = "202210423208"
 name = "刘义天"
 
 
+
 # 加载数据并添加非线性特征
 def load_data(filepath):
     """
@@ -96,6 +97,22 @@ def train_decision_tree(X, y):
     return clf
 
 
+# 对率回归预测函数
+def predict_logreg(inX, weights):
+    """
+    对率回归预测函数。
+
+    Args:
+    - inX (numpy array): 输入待分类的样本。
+    - weights (numpy array): 训练得到的权重。
+
+    Returns:
+    - int: 预测的分类标签。
+    """
+    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):
     """
@@ -110,8 +127,7 @@ def predict_fusion(inX, weights, clf):
     - int: 最终预测的分类标签。
     """
     # 对率回归预测
-    probability_logreg = 1 / (1 + np.exp(-np.dot(inX, weights)))
-    prediction_logreg = 1 if probability_logreg >= 0.4 else 0
+    prediction_logreg = predict_logreg(inX, weights)
 
     # 决策树预测
     prediction_tree = clf.predict(inX.reshape(1, -1))[0]