![]() ![]() Set the parameters C of class i to weight*C, for C-SVCĮ.g. Turns the shrinking heuristics off (default: on) Set tolerance of termination criterion (default: 0.001) Set cache memory size in MB (default: 40) Set the epsilon in loss function of epsilon-SVR (default: 0.1) WARNING: use only if your data has no missing values. WARNING: use only if your data is all numeric! Turns on normalization of input data (default: off) ![]() Set the parameter nu of nu-SVC, one-class SVM, and nu-SVR Set the parameter C of C-SVC, epsilon-SVR, and nu-SVR This generates the dll file in your current directory. Open the command prompt and do the following and press enter: ikvmc -out: .Set coef0 in kernel function (default: 0) This lets you use ikvm from command line. Set gamma in kernel function (default: 1/k) Set degree in kernel function (default: 3) Note = ,ġ = polynomial: (gamma*u'*v + coef0)^degreeĢ = radial basis function: exp(-gamma*|u-v|^2) LibSVM classifier (e.g., confusion matrix,precision, recall, ROC score,Ĭhih-Chung Chang, Chih-Jen Lin (2001). LibSVM reports many useful statistics about LibSVM allows users to experiment with One-class SVM, Regressing SVM, and LibSVM runs faster than SMO since it uses LibSVM to build the SVM classifier. A wrapper class for the libsvm tools (the libsvmĬlasses, typically the jar file, need to be in the classpath to use this
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