This is the command svm-train that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
NAME
svm-train - train one or more SVM instance(s) on a given data set to produce a model file
SYNOPSIS
svm-train [-s svm_type ] [ -t kernel_type ] [ -d degree ] [ -g gamma ] [ -r coef0 ] [ -c
cost ] [ -n nu ] [ -p epsilon ] [ -m cachesize ] [ -e epsilon ] [ -h shrinking ] [ -b
probability_estimates ] ] [ -wi weight ] [ -v n ] [ -q ]
training_set_file [ model_file ]
DESCRIPTION
svm-train trains a Support Vector Machine to learn the data indicated in the
training_set_file
and produce a model_file
to save the results of the learning optimization. This model can be used later with
svm_predict(1) or other LIBSVM enabled software.
OPTIONS
-s svm_type
svm_type defaults to 0 and can be any value between 0 and 4 as follows:
0 -- C-SVC
1 -- nu-SVC
2 -- one-class SVM
3 -- epsilon-SVR
4 -- nu-SVR
-t kernel_type
kernel_type defaults to 2 (Radial Basis Function (RBF) kernel) and can be any value
between 0 and 4 as follows:
0 -- linear: u.v
1 -- polynomial: (gamma*u.v + coef0)^degree
2 -- radial basis function: exp(-gamma*|u-v|^2)
3 -- sigmoid: tanh(gamma*u.v + coef0)
4 -- precomputed kernel (kernel values in training_set_file) --
-d degree
Sets the degree of the kernel function, defaulting to 3
-g gamma
Adjusts the gamma in the kernel function (default 1/k)
-r coef0
Sets the coef0 (constant offset) in the kernel function (default 0)
-c cost
Sets the parameter C ( cost ) of C-SVC, epsilon-SVR, and nu-SVR (default 1)
-n nu Sets the parameter nu of nu-SVC, one-class SVM, and nu-SVR (default 0.5)
-p epsilon
Set the epsilon in the loss function of epsilon-SVR (default 0.1)
-m cachesize
Set the cache memory size to cachesize in MB (default 100)
-e epsilon
Set the tolerance of termination criterion to epsilon (default 0.001)
-h shrinking
Whether to use the shrinking
heuristics, 0 or 1 (default 1)
-b probability-estimates
probability_estimates is a binary value indicating whether to calculate probability
estimates when training the SVC or SVR model. Values are 0 or 1 and defaults to 0
for speed.
-wi weight
Set the parameter C (cost) of class i to weight*C, for C-SVC (default 1)
-v n Set n for n -fold cross validation mode
-q quiet mode; suppress messages to stdout.
Use svm-train online using onworks.net services