模式识别与人工智能
模式識彆與人工智能
모식식별여인공지능
Moshi Shibie yu Rengong Zhineng
2013年
11期
1010-1018
,共9页
区间约简%约简模型%约简算法
區間約簡%約簡模型%約簡算法
구간약간%약간모형%약간산법
Interval Reduction%Reduction Model%Reduction Algorithm
无论基于分类质量还是基于相对正域的变精度粗糙集区间约简模型都存在多种异常，根本原因是约简过程中条件类的粒度发生变化，且分类质量、相对正域和下近似分布三者不再等价变化。为消除现有约简模型存在的约简异常，文中基于下近似分布不变重新定义了区间约简模型，并给出一种基于有序分辨矩阵的区间约简方法。最后将3种区间约简模型分别应用于Wine数据集，演示不同约简模型结果间的联系与区别。
無論基于分類質量還是基于相對正域的變精度粗糙集區間約簡模型都存在多種異常，根本原因是約簡過程中條件類的粒度髮生變化，且分類質量、相對正域和下近似分佈三者不再等價變化。為消除現有約簡模型存在的約簡異常，文中基于下近似分佈不變重新定義瞭區間約簡模型，併給齣一種基于有序分辨矩陣的區間約簡方法。最後將3種區間約簡模型分彆應用于Wine數據集，縯示不同約簡模型結果間的聯繫與區彆。
무론기우분류질량환시기우상대정역적변정도조조집구간약간모형도존재다충이상，근본원인시약간과정중조건류적립도발생변화，차분류질량、상대정역화하근사분포삼자불재등개변화。위소제현유약간모형존재적약간이상，문중기우하근사분포불변중신정의료구간약간모형，병급출일충기우유서분변구진적구간약간방법。최후장3충구간약간모형분별응용우Wine수거집，연시불동약간모형결과간적련계여구별。
Interval reduction models based on classification quality and positive region lead to different kinds of reduction anomalies in variable precision rough set model ( VPRS-Model) . The reason is that the size of condition classification changes with the reduction of condition attributes, besides, classification quality, positive region and lower approximation distribution do not change equivalently any more. A reduction model based on lower approximation distribution is defined to avoid all kinds of reduction anomalies and an interval reduction method is presented based on ordered discernibility matrix. At last, the application of 3 kinds of interval reduction model on Wine Dataset illustrates the relationship of different reduction models.
