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libsvm-2.88
  • Classification:Windows/.NET - GUI Develop
  • Development Tool:matlab
  • Sise:550 KB
  • Upload time:2011/6/25 5:49:31
  • Uploader:yuuu1989
  • Download Statistics:
Description
libsvm-2.88




File list:
libsvm-2.88
..........\java
..........\....\libsvm
..........\....\......\svm.java
..........\....\......\svm.m4
..........\....\......\svm_model.java
..........\....\......\svm_node.java
..........\....\......\svm_parameter.java
..........\....\......\svm_problem.java
..........\....\libsvm.jar
..........\....\Makefile
..........\....\svm_predict.java
..........\....\svm_scale.java
..........\....\svm_toy.java
..........\....\svm_train.java
..........\....\test_applet.html
..........\python
..........\......\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
..........\.......\python
..........\.......\......\svmc.pyd
..........\.......\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.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-2.91] - Face recognition based on c source code, very rare piece of code source code integrity, and can be used directly.
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