Fast Attribute Reduction Algorithm Based on Row Storage
Liang Bao · 2015
The existing attribute reduction algorithms mainly focus on the area of resident data in the memory. To decrease the accessing disk I / O times,a row storage mode is proposed. In this mode,not all data are required storing in the main memory. During the reducing process,the sub divisions of same category are collected into one array to get the simplified decision table quickly. Meanwhile,the indiscernibility degree is introduced as the measurement of the attribute importance. Then,a fast attribute reduction algorithm is proposed. Its time complexity and space complexity are low. The examples and experimental results show the effectiveness and feasibility of the proposed algorithm.