Attribute Reduction for Abnormal Decision Table Based on Fractal Dimension

Attribute reduction is a core research topic of rough set, but classical attribute reduction algorithm and its extended algorithms base on decision tables with decision attributes and can not be applied to attribute reduction of abnormal decision tables without decision attributes. So, based on rough set theory, it studied abnormal decision tables in fractal dimension and presented a heuristic attribute reduction algorithm. To a certain extent, the algorithm can resolve the attribute reduction problem of abnormal decision tables and extend application of Rough Set Theory. The example shows that the algorithm is effective and feasible.