In this paper, we give a generalization of the rough topology and the core to numerical data by classifying objects in terms of the attribute values. New approach to find the core for numerical data is discussed. Then a measurement to find whether an attribute is in the core or not is given. This new method for finding the core is used for attribute reduction. It is tested and compared by using machine learning algorithms. Finally, the algorithms and codes to convert a data to pertinent data and to find core is also provided.
翻译:在本文中,我们通过根据属性值对对象进行分类,将粗图和核心数据与数字数据进行概括化。讨论了为数字数据寻找核心的新办法。然后讨论了为查找某个属性是否在核心中而确定一个属性的新办法。这种查找核心的新方法用于减少属性。它通过使用机器学习算法进行测试和比较。最后,还提供了将数据转换为相关数据和查找核心的算法和代码。