搜索资源列表
03-021
- 基于向量机的次优化浮动顺序算法FFSM的应用-Efficient Mining of Frequent Subgraph in the Presence of Isomorphism
ICDM03_2
- 基于向量机的次优化浮动顺序算法向量机的FFSM运用-Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
FFSM
- 浮动顺序搜索算法搜索特征空间生成候选子集-Sequential floating search algorithm to search a subset of the feature space generated candidate
frequent-subgraph
- 用于图集上子图搜索的代码，gSpan和FFSM的源码，都是在linux下运行，其中gSpan包括直接可以用shell运行的二进制文件和一个C&matlab版本，FFSM是C&matlab版本-Atlas subgraph search for the code, gSpan and FFSM source, are run under linux, which can be used directly gSpan including binaries and shell to run a C &
FFSM
- This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
laser-fiber
- this file deals with fiber laser using FFSM method