文件列表:

demoBagSVM (0, 2008-09-01)
demoBagSVM\BagSVM.m (6363, 2008-09-01)
demoBagSVM\demo.m (704, 2008-09-01)
demoBagSVM\build_Kbag.m (1629, 2008-07-09)
demoBagSVM\kernelmatrix.m (1191, 2008-05-23)
demoBagSVM\closerCluster.m (387, 2008-06-02)
demoBagSVM\code_svm (0, 2008-09-01)
demoBagSVM\code_svm\svmtrain.mexglx (68500, 2008-05-23)
demoBagSVM\code_svm\svmpredict.dll (28672, 2008-05-26)
demoBagSVM\code_svm\svmpredict.mexglx (64561, 2008-05-23)
demoBagSVM\code_svm\svmtrain.dll (49152, 2008-05-26)
demoBagSVM\code_svm\.DS_Store (6148, 2008-08-31)
demoBagSVM\unlabeled.txt (9117, 2008-08-31)
demoBagSVM\labeled.txt (549, 2008-08-31)
demoBagSVM\L2_distance.m (2067, 2007-10-05)

------------------------------------------- % Matlab demo for Bagged Support Vector Machines (BAGSVM) % http://www.uv.es/gcamps/bagsvm/ % % Devis Tuia (devis.tuia@unil.ch) % Gustavo Camps-Valls (gcamps@uv.es), 2008 ------------------------------------------- ------------------------------------------- Abstract: ------------------------------------------- This a MATLAB demo for implementing the semi-supervised bagged SVM for remote sensing data classification. If you find the method interesting and useful in your application, please also cite: "Semi-supervised Remote Sensing Image Classification with Cluster Kernels" Devis Tuia and Gustavo Camps-Valls IEEE Geoscience and Remote Sensing Letters 2008, submitte ------------------------------------------- How it works ... ------------------------------------------- Please take a look at the file "demo.m", which automatically runs the algorithms (both summation and product kernels) and compares it to the supervised SVM. This demo basically calls BagSVM.m with different parameters. The BagSVM.m file loads the two-moon problem and tests both the SVM and the BagSVM. There are some files called from this one: % Concerning the Bagging part build_Kbag.m Builds the kernel bag for training and testing L2_DISTANCE.m Computes Euclidean distance matrix kernelmatrix.m Computes the (training or testing) kernel matrices fast closerCluster.m Computes the cluster membership of a set of points based on Kmeans centers % Concerning the SVM part svmtrain.mexglx Train SVM methods and returns a model structure svmpredict.mexglx Test SVM methods using the model structure returned from svmtrain.mexglx [Windows .dll files and Mac support files can be downloaded from http://gpds.uv.es/~jordi/] ------------------------------------------- Copyright and disclaimer: ------------------------------------------- The programs are granted free of charge for research and education purposes only. Scientific results produced using the software provided shall acknowledge the use of the SemiSVR implementation provided by us. If you plan to use it for non-scientific purposes, don't hesitate to contact us. Because the programs are licensed free of charge, there is no warranty for the program, to the extent permitted by applicable law. except when otherwise stated in writing the copyright holders and/or other parties provide the program "as is" without warranty of any kind, either expressed or implied, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. the entire risk as to the quality and performance of the program is with you. should the program prove defective, you assume the cost of all necessary servicing, repair or correction. In no event unless required by applicable law or agreed to in writing will any copyright holder, or any other party who may modify and/or redistribute the program, be liable to you for damages, including any general, special, incidental or consequential damages arising out of the use or inability to use the program (including but not limited to loss of data or data being rendered inaccurate or losses sustained by you or third parties or a failure of the program to operate with any other programs), even if such holder or other party has been advised of the possibility of such damages.

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