为解决马田系统多分类算法存在的样本重复训练以及分类准确率下降等问题,文章提出了一种基于改进的类间相似方向数(Number of Inter-class Similarity Direction,NISD)的偏二叉树马田系统多分类算法。该算法利用马氏距离改进类间相似方...为解决马田系统多分类算法存在的样本重复训练以及分类准确率下降等问题,文章提出了一种基于改进的类间相似方向数(Number of Inter-class Similarity Direction,NISD)的偏二叉树马田系统多分类算法。该算法利用马氏距离改进类间相似方向数,获得更为科学的样本分类顺序,依此顺序自上而下生成整个偏二叉树,在非叶子节点构造马田系统二分类器,生成最终的分类模型。对于含k个类别的待分类样本,该算法只用训练k-1个二分类器,便可得到马田系统多分类模型,与此同时,层层剥离样本减少了样本的重复训练。UCI数据集实验结果表明,该算法分类效率更高,分类准确率也较高。展开更多
Some kinds of the self-similar sets with overlapping structures are studied by introducing the graph-directed constructions satisfying the open set condition that coincide with these sets. In this way, the dimensions ...Some kinds of the self-similar sets with overlapping structures are studied by introducing the graph-directed constructions satisfying the open set condition that coincide with these sets. In this way, the dimensions and the measures are obtained.展开更多
文摘为解决马田系统多分类算法存在的样本重复训练以及分类准确率下降等问题,文章提出了一种基于改进的类间相似方向数(Number of Inter-class Similarity Direction,NISD)的偏二叉树马田系统多分类算法。该算法利用马氏距离改进类间相似方向数,获得更为科学的样本分类顺序,依此顺序自上而下生成整个偏二叉树,在非叶子节点构造马田系统二分类器,生成最终的分类模型。对于含k个类别的待分类样本,该算法只用训练k-1个二分类器,便可得到马田系统多分类模型,与此同时,层层剥离样本减少了样本的重复训练。UCI数据集实验结果表明,该算法分类效率更高,分类准确率也较高。
基金Project supported by the National Natural Science Foundation of China and Mathematics Center ofMorningside, Chinese Academy Sc
文摘Some kinds of the self-similar sets with overlapping structures are studied by introducing the graph-directed constructions satisfying the open set condition that coincide with these sets. In this way, the dimensions and the measures are obtained.