LIBSVMLibrary for Support Vector Machines
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The proposed core set based LARM is evaluated on twenty datasets, including both LIBSVM datasets [24] and UCI datasets [25].
In table 3 we list the initialized values for all LIBSVM parameter we chosen.
To evaluate the performance of the MALDTP method, we conduct some experiments on two well-known databases (CK+ [44] and JAFFE [37]) by using LIBSVM [51] with Linear kernel and RBF kernel to classify the facial expressions, where the parameter C for RBF kernel is set to 100.
It is implemented in LIBSVM [41] and it is the approach used in this work.
Processing of data set; Initialize the current positions and the pbest positions of all particles which are binary bits with each representing whether the corresponding gene is selected or not; do Determine the mean best position among the particles by mbest = Get_mbest(pbest), select a suitable value for [beta]; for i = 1 to population size M Call the LIBSVM tool box to construct the SVM classifier and get the classification accuracy for the data; With the classification accuracy and the number of selected genes (i.
For the calculated LBP histogram, LIBSVM [15] is used for similarity measurement of text region and finally gives the text extraction results.
One of the most commonly used solvers is LIBSVM [19].
We used the LIBSVM implementation of SVMs for regression.
By using the software LIBSVM (Chang & Lin, 2007), we first found the best parameter C and [gamma] with crossvalidation, then used the best parameter C and [gamma] to train the whole training set, and finally tested over the testing set.
Extensions such as parameter optimization, feature selection, enhanced cross-validation (CV) options, the one-versus-all training scheme, and report generation were implemented in a C library on top of LIBSVM.
Two classic SVM regression methods, nu-SVR and epsilon-SVR, are provided by LIBSVM [23].
These data are trained on LIBSVM [16] with four methods respectively, namely the grid search method, bilinear search method, improved bilinear search method and bilinear grid search method.