From 74a81abb6a1cfbf72e363d2254e3dbc920abd2e4 Mon Sep 17 00:00:00 2001
From: 77 <3298722099@qq.com>
Date: Thu, 31 Oct 2024 17:06:55 +0800
Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20function.py?=
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---
 function.py | 27 +++++++++++++++++++++++----
 1 file changed, 23 insertions(+), 4 deletions(-)

diff --git a/function.py b/function.py
index b922be4..2ea5e48 100644
--- a/function.py
+++ b/function.py
@@ -25,6 +25,9 @@ id = "202210423201"
 name = "陈瑞琪祥"
 
 
+# 这里写自己的代码实现
+# 定义 Sigmoid 函数
+import numpy as np
 
 # 定义 Sigmoid 函数
 def sigmoid(z):
@@ -53,11 +56,27 @@ def predict_logreg(inX, weights):
 
 # 定义数据加载函数
 def load_data(filepath):
-    data = np.genfromtxt(filepath, delimiter=',', skip_header=1, filling_values=np.nan)
-    features = data[:, 1:-1]
-    labels = data[:, -1].astype(int)
-    return features, labels
+    """
+    从文件中加载数据。
 
+    Args:
+    - filepath (str): 数据文件路径。
+
+    Returns:
+    - np.array: 特征数据。
+    - np.array: 标签数据。
+    """
+    # 使用np.genfromtxt加载数据，并将'?'替换为np.nan
+    data = np.genfromtxt(filepath, delimiter=' ', skip_header=1, filling_values=np.nan)
+    
+    # 分离特征和标签
+    features = data[:, 1:-1]  # 假设除了第一列和最后一列外，其余都是特征
+    labels = data[:, -1]  # 假设最后一列是标签
+    
+    # 将标签转换为整数类型
+    labels = labels.astype(int)
+    
+    return features, labels
 if __name__ == "__main__":
     # 加载训练集
     X_train, y_train = load_data("./data/horse-colic.data")