Calculate confusion matrices of predicted and observed responses.
confusion(
x,
y = NULL,
cutoff = MachineShop::settings("cutoff"),
na.rm = TRUE,
...
)ConfusionMatrix(data = NA, ordered = FALSE)
factor of observed responses or resample result containing observed and predicted responses.
predicted responses if not contained in x
.
numeric (0, 1) threshold above which binary factor
probabilities are classified as events and below which survival
probabilities are classified. If NULL
, then binary responses are
summed directly over predicted class probabilities, whereas a default
cutoff of 0.5 is used for survival probabilities. Class probability
summations and survival will appear as decimal numbers that can be
interpreted as expected counts.
logical indicating whether to remove observed or predicted
responses that are NA
when calculating metrics.
arguments passed to other methods.
square matrix, or object that can be converted to one, of cross-classified predicted and observed values in the rows and columns, respectively.
logical indicating whether the confusion matrix row and columns should be regarded as ordered.
The return value is a ConfusionMatrix
class object that inherits from
table
if x
and y
responses are specified or a
ConfusionList
object that inherits from list
if x
is a
Resamples
object.
# NOT RUN {
res <- resample(Species ~ ., data = iris, model = GBMModel)
(conf <- confusion(res))
plot(conf)
# }
Run the code above in your browser using DataLab