The function applies a model (classification or regression) produced by the
LiblineaR function to every row of a
data matrix and returns the model predictions.
# S3 method for LiblineaR predict(object, newx, proba = FALSE, decisionValues = FALSE, ...)
Object of class
"LiblineaR", created by
An n x p matrix containing the new input data. A vector will be transformed to a n x 1 matrix. A sparse matrix (from SparseM package) will also work.
Logical indicating whether class probabilities should be
computed and returned. Only possible if the model was fitted with
type=7, i.e. a Logistic Regression.
Logical indicating whether model decision values should
be computed and returned. Only possible for classification models
type<10). Default is
Currently not used
By default, the returned value is a list with a single entry:
A vector of predicted labels (or values for regression).
An n x k matrix (k number of classes) of the class probabilities. The columns of this matrix are named after class labels.
An n x k matrix (k number of classes) of the model decision values. The columns of this matrix are named after class labels.
For more information on 'LIBLINEAR' itself, refer to: R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. LIBLINEAR: A Library for Large Linear Classification, Journal of Machine Learning Research 9(2008), 1871-1874. http://www.csie.ntu.edu.tw/~cjlin/liblinear