generated from LufsX/Experiment-LogReg
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+28
-7
@@ -81,18 +81,39 @@ def load_data(filepath):
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"""
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data = []
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labels = []
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# 读取数据并处理缺失值
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with open(filepath, 'r') as file:
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for line in file:
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fields = line.strip().split()
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if '?' in fields or len(fields) < 2:
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continue
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try:
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data.append([float(x) for x in fields[:-1]])
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labels.append(int(fields[-1]))
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except ValueError:
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if len(fields) < 2:
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continue
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return np.array(data), np.array(labels)
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features = fields[:-1]
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label = fields[-1]
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# 记录特征和标签
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data.append(features)
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labels.append(label)
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# 转换数据为 NumPy 数组,方便进一步处理
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data = np.array(data)
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labels = np.array(labels, dtype=int)
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# 用于存储浮点型数据
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numeric_data = np.zeros(data.shape, dtype=float)
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# 对每列进行缺失值填补
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for col in range(data.shape[1]):
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# 获取列数据,将 "?" 替换为 NaN,然后计算均值
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col_data = np.where(data[:, col] == '?', np.nan, data[:, col]).astype(float)
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mean_value = np.nanmean(col_data) # 计算均值忽略 NaN
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# 将 NaN 替换为均值
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col_data = np.where(np.isnan(col_data), mean_value, col_data)
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numeric_data[:, col] = col_data
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return numeric_data, labels
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if __name__ == "__main__":
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