performance-class {ROCR} | R Documentation |
Class performance
Description
Object to capture the result of a performance evaluation, optionally collecting evaluations from several cross-validation or bootstrapping runs.
Details
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, andalpha.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 inalpha.values
, whilex.values
andy.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 iny.values
, while the corresponding values of the obligatory axis are stored inx.values
, andalpha.values
is empty.
A performance measure whose value is just a scalar (e.g.
performance( predObj, 'auc' )
). The value is then stored iny.values
, whilex.values
andalpha.values
are empty.
Slots
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 eithernone
orcutoff
.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]]
, andalpha.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 from the Class
Objects can be created by using the performance
function.
Author(s)
Tobias Sing tobias.sing@gmail.com, Oliver Sander osander@gmail.com
References
A detailed list of references can be found on the ROCR homepage at http://rocr.bioinf.mpi-sb.mpg.de.
See Also
prediction
performance
,
prediction-class
,
plot.performance