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  • Update : 2012-11-26
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Introduction - If you have any usage issues, please Google them yourself
A vector machine (svm) the sequential minimal optimization algorithm source code, the algorithm can be used to develop parallel algorithms svm!
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(Preview for download)
smosvm\mapredsvm\An improved training algorithm for svm 1997.pdf
......\.........\chunking\bit reduction svm.pdf
......\.........\........\chunking with svm.pdf
......\.........\........\distributed svm learning and support vctor reduction.pdf
......\.........\........\double chunking for solving svms for very large datasets.pdf
......\.........\........\making large ssale svm learning practical.ps\joachims_99a.log
......\.........\........\............................................\joachims_99a.pdf
......\.........\........\............................................\joachims_99a.ps
......\.........\CSD-04-1307.pdf
......\.........\dm04_012boleyd.pdf
......\.........\Fast kernel learning using smo8.27.pdf
......\.........\fast training of structured svm using fixed-threshold SMO 8.27.pdf
......\.........\good paper.pdf
......\.........\good paper2.pdf
......\.........\HadoopMapreduce.pdf
......\.........\ICPR_SVM.pdf
......\.........\ieee_smo_reg.ps\ieee_smo_reg.log
......\.........\...............\ieee_smo_reg.pdf
......\.........\...............\ieee_smo_reg.ps
......\.........\improvements to platts smo algorithm.pdf
......\.........\lssvmsmo_nc_keerthi_03.pdf
......\.........\ManjrasoftAnekaFlyer-LifeScienceSector.pdf
......\.........\Max-margin learning Gaussian Mixtures with smo8.27.pdf
......\.........\potsmo.pdf
......\.........\skm_icml.pdf
......\.........\smo-book.pdf
......\.........\smo-mapreduce.pdf
......\.........\smo.pdf
......\.........\smo1.pdf
......\.........\smoTR.pdf
......\.........\smo_mod.pdf
......\.........\using analytic QP and sparseness to speed training of svm 8.27.pdf
......\.........\chunking\making large ssale svm learning practical.ps
......\.........\chunking
......\.........\ieee_smo_reg.ps
......\mapredsvm
smosvm
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