Title:
libsvm-3.1-[FarutoUltimate3.1Mcode]
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Description: As the basis of the whole network security situation awareness, the quality of situation elements extraction will directly affect the performance of the situation awareness system. To solve the problem that the situation element is difficult to extract, we propose a method to extract the hierarchical frame situation elements based on the enhanced probabilistic neural network. In the hierarchical access frame, we use the principal component analysis (PCA) to reduct the training sample attribute and to process the special attribute encoding fusion. The result can be used to optimize the structure of the probabilistic neural network (PNN) and reduce the system complexity. Take PNN as the base classifier to form the final strong classifier by repeated iteration, weight replacement and weighted fusion. The experimental results show that the scheme is an effective method to obtain the situation factors and its accuracy is 95.53%,which is significantly better than other algorithms.
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File list (Check if you may need any files):
tools\checkdata.py
tools\easy.py
tools\grid.py
tools\README
tools\subset.py
windows\libsvm.dll
windows\libsvmread.mexw32
windows\libsvmread.mexw64
windows\libsvmwrite.mexw32
windows\libsvmwrite.mexw64
windows\svm-predict.exe
windows\svm-scale.exe
windows\svm-toy.exe
windows\svm-train.exe
windows\svmpredict.mexw32
windows\svmpredict.mexw64
windows\svmtrain.mexw32
windows\svmtrain.mexw64
svm.cpp.bak
svm-predict.c
svm-scale.c
svm-train.c
svm.h
svm.cpp
svm.def
FAQ.html
Makefile.win
COPYRIGHT
heart_scale
Makefile
README
java\libsvm\svm.java
java\libsvm\svm.m4
java\libsvm\svm_model.java
java\libsvm\svm_node.java
java\libsvm\svm_parameter.java
java\libsvm\svm_print_interface.java
java\libsvm\svm_problem.java
java\libsvm.jar
java\Makefile
java\svm_predict.java
java\svm_scale.java
java\svm_toy.java
java\svm_train.java
java\test_applet.html
matlab\heart_scale.mat
matlab\libsvmread.c
matlab\libsvmread.mexw32
matlab\libsvmwrite.c
matlab\libsvmwrite.mexw32
matlab\make.m
matlab\Makefile
matlab\README
matlab\svm.obj
matlab\svmpredict.c
matlab\svmpredict.mexw32
matlab\svmtrain.c
matlab\svmtrain.c.bak
matlab\svmtrain.mexw32
matlab\svm_model_matlab.c
matlab\svm_model_matlab.h
matlab\svm_model_matlab.obj
matlab-implement[by faruto]\a_template_flow_usingSVM_class.m
matlab-implement[by faruto]\a_template_flow_usingSVM_regress.m
matlab-implement[by faruto]\ClassResult.m
matlab-implement[by faruto]\ClassResult_test.m
matlab-implement[by faruto]\gaSVMcgForClass.m
matlab-implement[by faruto]\gaSVMcgForRegress.m
matlab-implement[by faruto]\gaSVMcgpForRegress.m
matlab-implement[by faruto]\libsvm参数说明.txt
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\bs2rv.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\contents.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbase.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtrp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\migrate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mpga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutbga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mytest\gaSVM.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\ranking.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recdis.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recint.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reclin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recmut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recombin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reins.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rep.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\resplot.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rws.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\scaling.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\select.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\sus.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdprs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovmp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsh.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovshrs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsp.m
