文件名称:MILL
介绍说明－－下载内容均来自于网络，请自行研究使用
模式识别中，多标签标记中的经典代码，主要用于场景分类，目标识别，结合svm和boost算法对自然场景进行分类，真的很不错，看看吧-Pattern Recognition, multi-tagged in the classic code, mainly used for scene classification, object recognition, combined with svm and boost the natural scene classification algorithm, it is really good, let' s see it
(系统自动生成,下载前可以参看下载内容)
下载文件列表
MIL_Classify.m
example.data
bag2instance.m
Classify.m
prob2label.m
evaluate_by_inst_choice.m
OutputRet.m
strtrim.m
splitarray.m
strsplit.m
GetClassSet.m
ParseCmd.m
svm
...\elephant.sil.data
...\elephant.sil.data.model
...\LICENSE.txt
...\mySVM.exe
...\mySVMpredict.exe
...\output.txt
...\param2.dat
...\param_1Class.dat
...\param_RBF.dat
...\svmpredict.exe
...\svmscale.exe
...\svmtoy.exe
...\svmtrain.exe
...\svm_classify.exe
...\svm_learn.exe
...\temp.train.txt
...\temp.train.txt.model
ReadInput.pl
MIL_Train_Validate.m
MIL_Train_Test_Validate.m
MIL_Train_Test_Simple.m
MIL_Test_Validate.m
MIL_Size.m
MIL_Scale.m
MIL_Run.m
MIL_Leave_One_Out.m
MIL_Inst_Evaluate.m
MIL_Data_Save.m
MIL_Data_Load.m
MIL_Cross_Validate.m
MIL_Bag_Evaluate.m
mil2sil.m
kNN.m
iterdiscrim_APR.m
EMDD.m
DD.m
bag_MI_SVM.m
sparse_example.data
ParseParameter.m
example2.data
inst_MI_SVM.m
LibSVM.m
example.data
bag2instance.m
Classify.m
prob2label.m
evaluate_by_inst_choice.m
OutputRet.m
strtrim.m
splitarray.m
strsplit.m
GetClassSet.m
ParseCmd.m
svm
...\elephant.sil.data
...\elephant.sil.data.model
...\LICENSE.txt
...\mySVM.exe
...\mySVMpredict.exe
...\output.txt
...\param2.dat
...\param_1Class.dat
...\param_RBF.dat
...\svmpredict.exe
...\svmscale.exe
...\svmtoy.exe
...\svmtrain.exe
...\svm_classify.exe
...\svm_learn.exe
...\temp.train.txt
...\temp.train.txt.model
ReadInput.pl
MIL_Train_Validate.m
MIL_Train_Test_Validate.m
MIL_Train_Test_Simple.m
MIL_Test_Validate.m
MIL_Size.m
MIL_Scale.m
MIL_Run.m
MIL_Leave_One_Out.m
MIL_Inst_Evaluate.m
MIL_Data_Save.m
MIL_Data_Load.m
MIL_Cross_Validate.m
MIL_Bag_Evaluate.m
mil2sil.m
kNN.m
iterdiscrim_APR.m
EMDD.m
DD.m
bag_MI_SVM.m
sparse_example.data
ParseParameter.m
example2.data
inst_MI_SVM.m
LibSVM.m