predict.LiblineaR.ACF: Predictions with LiblineaR.ACF model

Description Usage Arguments Value Note Author(s) References See Also

Description

The function applies a classification model produced by the LiblineaR.ACF function to every row of a data matrix and returns the model predictions.

Usage

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## S3 method for class 'LiblineaR.ACF'
predict(object, newx, decisionValues = FALSE, ...)

Arguments

object

Object of class "LiblineaR.ACF", created by LiblineaR.ACF.

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 FALSE.

...

Currently not used

Value

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.

Note

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.

Author(s)

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

References

See Also

LiblineaR.ACF


aydindemircioglu/LiblineaR.ACF documentation built on May 11, 2019, 4:13 p.m.