文件名称:MIL-learners
- 所属分类:
- 人工智能/神经网络/遗传算法
- 资源属性:
- [Matlab] [源码]
- 上传时间:
- 2015-03-15
- 文件大小:
- 3.86mb
- 下载次数:
- 0次
- 提 供 者:
- 吴*
- 相关连接:
- 无
- 下载说明:
- 别用迅雷下载,失败请重下,重下不扣分!
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全称是:MIL learners and their ensemble versions一个很好的lazy learnng matlab 程序-MIL learners and their ensemble versions
(系统自动生成,下载前可以参看下载内容)
下载文件列表
MIL learners and their ensemble versions
........................................\Data Preparation
........................................\................\auxiliary
........................................\................\.........\divide_10fold_Musk1.m
........................................\................\.........\divide_10fold_Musk2.m
........................................\................\.........\min_max_norm.m
........................................\................\musk data from UCI ML Repository
........................................\................\................................\clean1.data
........................................\................\................................\...........\clean1.data
........................................\................\................................\clean1.data.Z
........................................\................\................................\clean1.info
........................................\................\................................\clean1.names
........................................\................\................................\clean2.data
........................................\................\................................\...........\clean2.data
........................................\................\................................\clean2.data.Z
........................................\................\................................\clean2.info
........................................\................\................................\clean2.names
........................................\................\................................\Index
........................................\................\Preprocessed data
........................................\................\.................\Musk1
........................................\................\.................\.....\all.txt
........................................\................\.................\.....\molecule_num.TXT
........................................\................\.................\Musk2
........................................\................\.................\.....\all.txt
........................................\................\.................\.....\molecule_num.TXT
........................................\Ensemble Algorithm
........................................\..................\APR
........................................\..................\...\Bagging_APR_Musk1.m
........................................\..................\...\Bagging_APR_Musk2.m
........................................\..................\auxiliary function
........................................\..................\..................\copy.m
........................................\..................\C-kNN
........................................\..................\.....\Bagging_C_kNN_Musk1.m
........................................\..................\.....\Bagging_C_kNN_Musk2.m
........................................\..................\Diverse Density
........................................\..................\...............\Bagging_DD_Musk1.m
........................................\..................\...............\Bagging_DD_Musk2.m
........................................\..................\EM-DD
........................................\..................\.....\Bagging_EMDD_Musk1.m
........................................\..................\.....\Bagging_EMDD_Musk2.m
........................................\Individual Algorithm
........................................\....................\Citation KNN
........................................\....................\............\CKNN.m
........................................\....................\............\minHausdorff.m
........................................\....................\Diverse Density
........................................\....................\...............\dfpmin.m
........................................\....................\...............\DInstance.m
...........................