Feng Honghai
ABSTRACT
Because of the amount of missing values in our SARS data set is very large, to fill in them wholly with the existing methods is impossible or the results of being filled in are not reliable. Only taking two attributes into account can avoid using the large amount of missing values, which is the feature of rough set that other machine learning method cannot hold. In this paper, we induced some rules based on rough set from the SARS data set that have not been detected by medical experts in clinic practice.
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Digital Library
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Index Terms
- Using rough set to induce dependencies between attributes where there are a large amount of missing values: a SARS data application
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