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验证算法公平性与数据集性质

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# 验证算法公平性与完整性 # 开始

# 传入pandas dateframe作为数据集 dataset = Analyse(pandas_dataframe)

# 验证完整性 result = Analyse.completeness(col_name) # col_name 数据列名,返回有多少空值

# 验证公平性 dataset.new_test # 将pandas_dataframe中的敏感属性所在列随机打乱,重新赋值,然后再进行实验

# 查看数据分布 dataset.dis_analyse(‘x’, ‘y’) # 输出y相对于x的分布图像

# 比较两次实验结果差异 dataset.compare(x, y) # 输入两次结果x, y(二者均为torch向量),比较KL散度,越大说明相差越大

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