Model Performance Metrics
Compute measures of model performance.
performance(x, ...)
## S3 method for class 'BinomialVariate'
performance(
x,
y,
metrics = MachineShop::settings("metrics.numeric"),
na.rm = TRUE,
...
)
## S3 method for class 'factor'
performance(
x,
y,
metrics = MachineShop::settings("metrics.factor"),
cutoff = MachineShop::settings("cutoff"),
na.rm = TRUE,
...
)
## S3 method for class 'matrix'
performance(
x,
y,
metrics = MachineShop::settings("metrics.matrix"),
na.rm = TRUE,
...
)
## S3 method for class 'numeric'
performance(
x,
y,
metrics = MachineShop::settings("metrics.numeric"),
na.rm = TRUE,
...
)
## S3 method for class 'Surv'
performance(
x,
y,
metrics = MachineShop::settings("metrics.Surv"),
cutoff = MachineShop::settings("cutoff"),
na.rm = TRUE,
...
)
## S3 method for class 'ConfusionList'
performance(x, ...)
## S3 method for class 'ConfusionMatrix'
performance(x, metrics = MachineShop::settings("metrics.ConfusionMatrix"), ...)
## S3 method for class 'Resamples'
performance(x, ...)x |
observed responses; or confusion or resample result containing observed and predicted responses. |
... |
arguments passed from the |
y |
predicted responses if not contained in |
metrics |
metric function, function name, or vector of these with which to calculate performance. |
na.rm |
logical indicating whether to remove observed or predicted
responses that are |
cutoff |
numeric (0, 1) threshold above which binary factor probabilities are classified as events and below which survival probabilities are classified. |
## Requires prior installation of suggested package gbm to run res <- resample(Species ~ ., data = iris, model = GBMModel) (perf <- performance(res)) summary(perf) plot(perf) ## Survival response example library(survival) gbm_fit <- fit(Surv(time, status) ~ ., data = veteran, model = GBMModel) obs <- response(gbm_fit, newdata = veteran) pred <- predict(gbm_fit, newdata = veteran, type = "prob") performance(obs, pred)
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.