Description Details Slots Objects from the Class Author(s) References See Also
Object to capture the result of a performance evaluation, optionally collecting evaluations from several cross-validation or bootstrapping runs.
A performance
object can capture information from four
different evaluation scenarios:
The behaviour of a cutoff-dependent performance measure across
the range of all cutoffs (e.g. performance( predObj, 'acc' )
). Here,
x.values
contains the cutoffs, y.values
the
corresponding values of the performance measure, and
alpha.values
is empty.
The trade-off between two performance measures across the
range of all cutoffs (e.g. performance( predObj,
'tpr', 'fpr' )
). In this case, the cutoffs are stored in
alpha.values
, while x.values
and y.values
contain the corresponding values of the two performance measures.
A performance measure that comes along with an obligatory
second axis (e.g. performance( predObj, 'ecost' )
). Here, the measure values are
stored in y.values
, while the corresponding values of the
obligatory axis are stored in x.values
, and alpha.values
is empty.
A performance measure whose value is just a scalar
(e.g. performance( predObj, 'auc' )
). The value is then stored in
y.values
, while x.values
and alpha.values
are
empty.
x.name
Performance measure used for the x axis.
y.name
Performance measure used for the y axis.
alpha.name
Name of the unit that is used to create the parametrized
curve. Currently, curves can only be parametrized by cutoff, so
alpha.name
is either none
or cutoff
.
x.values
A list in which each entry contains the x values of the curve
of this particular cross-validation run. x.values[[i]]
,
y.values[[i]]
, and alpha.values[[i]]
correspond to each
other.
y.values
A list in which each entry contains the y values of the curve of this particular cross-validation run.
alpha.values
A list in which each entry contains the cutoff values of the curve of this particular cross-validation run.
Objects can be created by using the performance
function.
Tobias Sing tobias.sing@gmail.com, Oliver Sander osander@gmail.com
A detailed list of references can be found on the ROCR homepage at http://rocr.bioinf.mpi-sb.mpg.de.
prediction
performance
,
prediction-class
,
plot.performance
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.