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- W2360447941 abstract "An effective rough-set-based method is developed to study the key problem of process distributed mass data,which is the problem of segment massive dataset.Most other rough-set-based algorithms are designed only for memory-resident data,so it is hard for these algorithms to deal with mass data set.On the base of definition of best partition,and combined with the idea of attribute reduction,a mass data partition for rough set on attribute reduction algorithm is developed for processing mass data sets directly.It is proved by simulation experiments that the MDPRS-AR method presented is faster than original rough-set-based algorithms by about 70%,while its performance is close to those algorithms that process the original data set as a whole." @default.
- W2360447941 created "2016-06-24" @default.
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- W2360447941 date "2010-01-01" @default.
- W2360447941 modified "2023-09-23" @default.
- W2360447941 title "Mass Data Partition for Rough Set on Attribute Reduction Algorithm" @default.
- W2360447941 hasPublicationYear "2010" @default.
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