Description Usage Arguments Value Note Author(s) References See Also
The function applies a classification model produced by the LiblineaR.ACF
function to every row of a
data matrix and returns the model predictions.
1 2 |
object |
Object of class |
newx |
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. |
decisionValues |
Logical indicating whether model decision values should
be computed and returned. Default is |
... |
Currently not used |
By default, the returned value is a list with a single entry:
predictions |
A vector of predicted labels. |
If decisionValues
is set to TRUE
, an additional entry is returned:
decisionValues |
An n x k matrix (k number of classes) of the model decision values. The columns of this matrix are named after class labels. |
If the data on which the model has been fitted have been centered
and/or scaled, it is very important to apply the same process on the
newx
data as well, with the scale and center values of the training
data.
Thibault Helleputte thibault.helleputte@dnalytics.com and
Pierre Gramme pierre.gramme@dnalytics.com.
Modified by Aydin Demircioglu.
Based on C/C++-code by Chih-Chung Chang and Chih-Jen Lin
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
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