※ 引述《freelance978 (阿什坎迪)》之铭言： : 刚刚阅读有关Hybrid K-medoid Algorithm的文章 : 他有提到三个步骤 1选择 2交配 3突变 : 染色体编码方式是整数编码(Integer Representation) : 每笔资料会被依序编号 1,2,…,n，其中 n 为资料的总笔数。 : 将每一条染色体固定长度为 K，K为分群数， : 且每一条染色体里的每一个基因(gene)放入的可以是任何一笔资料的编号 1,2,…,n : 而这染色体的 K 个基因里的数字，分别地代表某一群资料集的群集中心资料点之编号。 : ex:若资料集中有 10 笔资料（给予编号 1..10），欲分成 3 群(K=3)， : 其随机产生的染色体表示假设为： 2 5 8 ，代表的意思是资料集分成三群後 : 各群中心 : 我要问的是他提到的交配跟突变方法: : 交配: 混合子集重组交配法(Mix Subset Recombination Crossover) : 突变: Flip Mutation : 有人听过这两个方法吗 : 查过他的ref 还是没写得很清楚 : 谢谢 上面有写啊。 以下节录自 "A Hybrid Algorithm for K-medoid Clustering of Large Data Sets" Wrote by W. Sheng and X. Liu: In order to avoid producing illegal individuals or producing offspring identical to the parents, we apply the mix subset recombination crossover [5], which has a built-in mutation with probability of Pm,mix. Given two parent individuals X1 and X2 with k features, mix subset recombination crossover works as follows: (1) Mix X1 and X2 to obtian Xmix by appending one parent individual to another and then the features of resulting Xmix are randomly scrabled. (2) Perform flip mutation on each feature of Xmix with a predetermined probability Pm,mix and then randomly scrable the features of Xmix again. (3) Build the offspring X3 by coping features from Xmix starting at the leftmost feature and going featurewise to the right, subject to the condition that features already in X3 are skipped. (4) Build the offspring X4 by coping features from Xmix starting at the rightmost feature and going featurewise to the left. subject to the condition that features already in X4 are skipped. The crossover is applied on each paired parent with probability of Pc. After crossover, the probability Pm of flip mutation will be applied to the offspring. Flip mutation replaces the chosen feature by another randomly generated feature, subject to the restriction that the new feature is not presented in the current genotype of the individual. 哪边看不懂？需要讲解吗？ --

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