A Feature Subset Selection Algorithm Based on Neighborhood Rough Set for Incremental Updating Datasets
Juan-ying XIE · Computer Technology and Development · 2011
A feature subset selection algorithm is presented based on neighborhood rough set theory for the datasets which are updated by the increment in their samples.It is well known that the increment in samples can cause the changeable in the reduction of attributes of the dataset.Did a through-paced analysis to the variety on positive region brought by the new added sample to the dataset,and discussed the selective updating to the feature subset(attribute reduction) according to all the cases.The selective updating to the original reduction of attributes of the dataset can avoid the unwanted operations,and reduce the complexity of the feature subset selection algorithm.Finally,gave a real example and demonstrated the algorithm.