文件名称:gmkl
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [MacOS] [Matlab] [源码]
- 上传时间：
- 2014-10-14
- 文件大小：
- 4.64mb
- 下载次数：
- 0次
- 提 供 者：
- 许*
- 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！
介绍说明－－下载内容均来自于网络，请自行研究使用
这是一般的多核学习，学习到的每一种特征用不同的核表示并用和或积的形式组合在一起，实现行为识别。-This is a general multicore learning, learning to use each feature represents a different nuclear and combined or integrated with, and form, to achieve behavior recognition.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
gmkl
....\GMKL
....\....\COMPGDoptimize.m
....\....\GMKL-EndUserLicenseAgreement.doc
....\....\GMKLwrapper.m
....\....\libsvm-3.18
....\....\...........\COPYRIGHT
....\....\...........\FAQ.html
....\....\...........\heart_scale
....\....\...........\java
....\....\...........\....\libsvm
....\....\...........\....\libsvm.jar
....\....\...........\....\......\svm.java
....\....\...........\....\......\svm.m4
....\....\...........\....\......\svm_model.java
....\....\...........\....\......\svm_node.java
....\....\...........\....\......\svm_parameter.java
....\....\...........\....\......\svm_print_interface.java
....\....\...........\....\......\svm_problem.java
....\....\...........\....\Makefile
....\....\...........\....\svm_predict.java
....\....\...........\....\svm_scale.java
....\....\...........\....\svm_toy.java
....\....\...........\....\svm_train.java
....\....\...........\....\test_applet.html
....\....\...........\Makefile
....\....\...........\Makefile.win
....\....\...........\matlab
....\....\...........\matlab.mat
....\....\...........\......\data.mat
....\....\...........\......\libsvmread.c
....\....\...........\......\libsvmread.mexw64
....\....\...........\......\libsvmwrite.c
....\....\...........\......\libsvmwrite.mexw64
....\....\...........\......\make.m
....\....\...........\......\Makefile
....\....\...........\......\README
....\....\...........\......\svmpredict.c
....\....\...........\......\svmpredict.mexw64
....\....\...........\......\svmtrain.c
....\....\...........\......\svmtrain.mexw64
....\....\...........\......\svm_model_matlab.c
....\....\...........\......\svm_model_matlab.h
....\....\...........\python
....\....\...........\......\Makefile
....\....\...........\......\README
....\....\...........\......\svm.py
....\....\...........\......\svmutil.py
....\....\...........\README
....\....\...........\svm-predict.c
....\....\...........\svm-scale.c
....\....\...........\svm-toy
....\....\...........\.......\gtk
....\....\...........\.......\...\callbacks.cpp
....\....\...........\.......\...\callbacks.h
....\....\...........\.......\...\interface.c
....\....\...........\.......\...\interface.h
....\....\...........\.......\...\main.c
....\....\...........\.......\...\Makefile
....\....\...........\.......\...\svm-toy.glade
....\....\...........\.......\qt
....\....\...........\.......\..\Makefile
....\....\...........\.......\..\svm-toy.cpp
....\....\...........\.......\windows
....\....\...........\.......\.......\svm-toy.cpp
....\....\...........\svm-train.c
....\....\...........\svm.cpp
....\....\...........\svm.def
....\....\...........\svm.h
....\....\...........\tools
....\....\...........\.....\checkdata.py
....\....\...........\.....\easy.py
....\....\...........\.....\grid.py
....\....\...........\.....\README
....\....\...........\.....\subset.py
....\....\...........\windows
....\....\...........\.......\libsvm.dll
....\....\...........\.......\libsvmread.mexw64
....\....\...........\.......\libsvmwrite.mexw64
....\....\...........\.......\svm-predict.exe
....\....\...........\.......\svm-scale.exe
....\....\...........\.......\svm-toy.exe
....\....\...........\.......\svm-train.exe
....\....\...........\.......\svmpredict.mexw64
....\....\...........\.......\svmtrain.mexw64
....\....\toyexample.mat