print.svmmaj {SVMMaj} | R Documentation |
Print Svmmaj class
Description
Trained SVM model as output from svmmaj
.
The returning object consist of the following values:
- call
The function specifications which has been called.
- lambda
The regularization parameter of the penalty term which has been used.
- loss
The corresponding loss function value of the final solution.
- iteration
Number of iterations needed to evaluate the algorithm.
- X
The attribute matrix of
dim(X) = c(n,k)
.- y
The vector of length
n
with the actual class labels. These labels can be numeric[0 1]
or two strings.- classes
A vector of length
n
with the predicted class labels of each object, derived from q.tilde- Xtrans
The attribute matrix
X
after standardization and (if specified) spline transformation.- norm.param
The applied normalization parameters (see
normalize
).- splineInterval
The spline knots which has been used (see
isb
).- splineLength
Denotes the number of spline basis of each explanatory variable in
X
.- method
The decomposition matrices used in estimating the model.
- hinge
The hinge function which has been used (see
getHinge
).- beta
If identified, the beta parameters for the linear combination (only available for linear kernel).
- q
A vector of length
n
with predicted values of each object including the intercept.- nSV
Number of support vectors.
Usage
## S3 method for class 'svmmaj'
print(x, ...)
## S3 method for class 'svmmaj'
summary(object, ...)
## S3 method for class 'summary.svmmaj'
print(x, ...)
## S3 method for class 'svmmaj'
plot(x, ...)
Arguments
x |
the |
... |
further arguments passed to or from other methods. |
object |
the |