Parses a given list of options.
Valid options are:
-F
Set the loss function to minimize.
0 = hinge loss (SVM), 1 = log loss (logistic regression),
2 = squared loss (regression), 3 = epsilon insensitive loss (regression),
4 = Huber loss (regression).
(default = 0)
-L
The learning rate. If normalization is
turned off (as it is automatically for streaming data), then the
default learning rate will need to be reduced (try 0.0001).
(default = 0.01).
-R <double>
The lambda regularization constant (default = 0.0001)
-E <integer>
The number of epochs to perform (batch learning only, default = 500)
-C <double>
The epsilon threshold (epsilon-insenstive and Huber loss only, default = 1e-3)
-N
Don't normalize the data
-M
Don't replace missing values
-S <num>
Random number seed.
(default 1)
-output-debug-info
If set, classifier is run in debug mode and
may output additional info to the console
-do-not-check-capabilities
If set, classifier capabilities are not checked before classifier is built
(use with caution).