CAJ | 학술논문

大多数模糊k－modes的相关改进算法仅关注对象之间的距离，并未关注对象的空间分布对于聚类的影响。将距离和密度双度量的测度方法引入模糊k－modes算法进行改进，该方法将对象的空间分布考虑在内，从而以一种更加合理的方式更新对象的隶属度。通过来自于UCl机器学习库的数据集测试算法改进前与改进后的性能，算法改进后的聚类正确率高于改进前的，证明算法改进后性能更好。
대다수모호k－modes적상관개진산법부관주대상지간적거리，병미관주대상적공간분포대우취류적영향。장거리화밀도쌍도량적측도방법인입모호k－modes산법진행개진，해방법장대상적공간분포고필재내，종이이일충경가합리적방식경신대상적대속도。통과래자우UCl궤기학습고적수거집측시산법개진전여개진후적성능，산법개진후적취류정학솔고우개진전적，증명산법개진후성능경호。
This paper introduces the double measure means of distance and density into fuzzy k-modes algorithm to im-prove it's performance.The method takes account into spatial distribution of data objects,with a more proper way to update the degree of membership of data objects.Using the datasets come from UCl machine learning repository to test the per-formance of the former and improved algorithm.The correct rate of improved algorithm is higher than the former,which shows the performance of improved algorithm is better than the former.