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libsvm-2.91
  • Classification:Windows/.NET - C # Programming
  • Development Tool:Visual C++
  • Sise:512 KB
  • Upload time:2011/6/7 20:07:29
  • Uploader:srujanangg
  • Download Statistics:
Description
Face recognition based on c source code, very rare piece of code source code integrity, and can be used directly.




File list:
libsvm-2.91
..........\libsvm-2.91
..........\...........\java
..........\...........\....\libsvm
..........\...........\....\......\svm.java
..........\...........\....\......\svm.m4
..........\...........\....\......\svm_model.java
..........\...........\....\......\svm_node.java
..........\...........\....\......\svm_parameter.java
..........\...........\....\......\svm_print_interface.java
..........\...........\....\......\svm_problem.java
..........\...........\....\libsvm.jar
..........\...........\....\Makefile
..........\...........\....\svm_predict.java
..........\...........\....\svm_scale.java
..........\...........\....\svm_toy.java
..........\...........\....\svm_train.java
..........\...........\....\test_applet.html
..........\...........\python
..........\...........\......\Makefile
..........\...........\......\README
..........\...........\......\svm.py
..........\...........\......\svmutil.py
..........\...........\python_old
..........\...........\..........\cross_validation.py
..........\...........\..........\Makefile
..........\...........\..........\README
..........\...........\..........\setup.py
..........\...........\..........\svm.py
..........\...........\..........\svmc.i
..........\...........\..........\svmc_wrap.c
..........\...........\..........\svm_test.py
..........\...........\..........\test_cross_validation.py
..........\...........\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
..........\...........\tools
..........\...........\.....\checkdata.py
..........\...........\.....\easy.py
..........\...........\.....\grid.py
..........\...........\.....\README
..........\...........\.....\subset.py
..........\...........\windows
..........\...........\.......\libsvm.dll
..........\...........\.......\svm-predict.exe
..........\...........\.......\svm-scale.exe
..........\...........\.......\svm-toy.exe
..........\...........\.......\svm-train.exe
..........\...........\COPYRIGHT
..........\...........\FAQ.html
..........\...........\heart_scale
..........\...........\Makefile
..........\...........\Makefile.win
..........\...........\README
..........\...........\svm-predict.c
..........\...........\svm-scale.c
..........\...........\svm-train.c
..........\...........\svm.cpp
..........\...........\svm.def
..........\...........\svm.h
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Related source code
[libsvm-3.20] - this is a good library for support vector machines(svm) that can use for classification.
[use_libsvzm] - To use precomputed kernel, you must include sample serial number asthe first column of the training and testing data (assume your kernelmatrix is K, # of instances is n):
[libsvm-3.12] - code matlab svm ( suport vector machine )
[use_libsvm(1)] - ce source est utiliser pour la classification
[libsvm-ranksvm-3.18] - linear svm method for version 3.18
[libsvm-3.13] - toolbox path for svmlib
[libsvm-matlab] - libsvm library for machine learning
[libsvm_format] - Transform data to the format of an SVM package(libsvm)Each row represents one record[label] [index1]:[value1] [index2]:[value2] ...2‐class label: +1, ‐1n‐class label: 1..n
[libsvm-2.88] - libsvm-2.88
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