Abstract: Membership transformation has many practical applications. Existing membership transforming algorithms have some essential problems. For example, they cannot show which parts in the index membership are useful for the objective classification or which parts are of no use. Therefore, the redundant data in the index membership that do not contribute to objective classification are also used to calculate the objective membership. To overcome this problem, we design a kind of filter from the viewpoint of objective classification to identify and remove those redundant index memberships as well as the redundant data in the index membership, and extract the ``available values'' for the objective classification. A general transforming algorithm from index membership to the objective membership can be obtained. An application example is introduced to illustrate the transforming process.