print.svmmaj: Print Svmmaj class

In SVMMaj: Implementation of the SVM-Maj Algorithm

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).

• splineLengthDenotes the number of spline basis of each explanatory variable in X.

• methodThe 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 svmmaj object as result of svmmaj
...	further arguments passed to or from other methods.
object	the svmmaj object as result of svmmaj

SVMMaj documentation built on May 23, 2022, 9:05 a.m.