If set, classifier capabilities are not checked before classifier is built
(use with caution).
default: ["false"]
C
The epsilon threshold (epsilon-insenstive and Huber loss only, default = 1e-3)
default: ["0.001"]
E
The number of epochs to perform (batch learning only, default = 500)
default: ["500"]
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)
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).
default: ["0.01"]
M
Don't replace missing values
default: ["false"]
N
Don't normalize the data
default: ["false"]
R
The lambda regularization constant (default = 0.0001)
default: ["1.0E-4"]
S
Random number seed.
(default 1)
default: ["1"]
batch-size
The desired batch size for batch prediction (default 100).
default: []
num-decimal-places
The number of decimal places for the output of numbers in the model (default 2).
default: []
output-debug-info
If set, classifier is run in debug mode and
may output additional info to the console