print.svmmaj: Print Svmmaj class
In SVMMaj: Implementation of the SVM-Maj Algorithm

print.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, ...)