From 85c3ac6b710f61d2bfa5c9e06eafb66c10830fc8 Mon Sep 17 00:00:00 2001
From: Yijuehen <1906265724@qq.com>
Date: Wed, 13 Nov 2024 18:31:14 +0800
Subject: [PATCH] =?UTF-8?q?=E6=9B=B4=E6=96=B0=20function.py?=
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---
 function.py | 43 +++++++++++++++++++------------------------
 1 file changed, 19 insertions(+), 24 deletions(-)

diff --git a/function.py b/function.py
index b279245..43c724b 100644
--- a/function.py
+++ b/function.py
@@ -5,35 +5,30 @@ id = "202210423230"
 name = "尹家立"
 
 def load_data(filepath):
-    data, labels = [], []
-    with open(filepath, 'r') as f:
-        for line in f:
-            line = line.strip().split()
-            if len(line) >= 1 and line[-1].isdigit():
-                # 将特征值中的缺失值（“?”）替换为0，并将其余项转换为浮点数
-                line_data = [0 if x == '?' else float(x) for x in line[:-1]]
-                data.append(line_data)
-                # 保留标签原始的三分类标签
-                labels.append(int(line[-1]))
+    """
+    从文件中加载数据，处理缺失值，并确保标签维持原始三分类标签。
 
-    data = np.array(data)
-    labels = np.array(labels)
+    Args:
+    - filepath (str): 数据文件路径。
 
-    # 检查特征数量
-    num_features = data.shape[1]
+    Returns:
+    - np.array: 特征数据。
+    - np.array: 标签数据。
+    """
+    # 读取数据，将 '?' 替换为 NaN
+    data = np.genfromtxt(filepath, delimiter=' ', dtype=float, missing_values='?', filling_values=np.nan)
 
-    # 特征选择：去掉特征3（索引2）和特征24~28（索引23~26），确保索引有效
-    indices_to_delete = [2]  # 特征3
-    if num_features > 24:  # 确保特征数量足够
-        indices_to_delete += list(range(24, 27))  # 特征24到27（索引23到26）
+    # 用列均值填补缺失值
+    nan_indices = np.isnan(data)
+    col_means = np.nanmean(data, axis=0)
+    data[nan_indices] = np.take(col_means, np.where(nan_indices)[1])
 
-    # 删除指定特征列
-    data = np.delete(data, indices_to_delete, axis=1)
+    # 分离特征和标签
+    X = data[:, :-1]
+    y = data[:, -1]
 
-    # 保留三分类标签
-    target_variable = labels  # 不再合并任何标签，保持三分类
-
-    return data, target_variable
+    # 确保标签值保持三分类标签（例如，假设标签值分别为 1：存活，2：死亡，3：安乐死）
+    return X, y