A series of functions that retrieve model metric details.
h2o.metric(object, thresholds, metric, transform = NULL) h2o.F0point5(object, thresholds) h2o.F1(object, thresholds) h2o.F2(object, thresholds) h2o.accuracy(object, thresholds) h2o.error(object, thresholds) h2o.maxPerClassError(object, thresholds) h2o.mean_per_class_accuracy(object, thresholds) h2o.mcc(object, thresholds) h2o.precision(object, thresholds) h2o.tpr(object, thresholds) h2o.fpr(object, thresholds) h2o.fnr(object, thresholds) h2o.tnr(object, thresholds) h2o.recall(object, thresholds) h2o.sensitivity(object, thresholds) h2o.fallout(object, thresholds) h2o.missrate(object, thresholds) h2o.specificity(object, thresholds)
| object | An H2OModelMetrics object of the correct type. |
|---|---|
| thresholds | (Optional) A value or a list of values between 0.0 and 1.0. If not set, then all thresholds will be returned. If "max", then the threshold maximizing the metric will be used. |
| metric | (Optional) the metric to retrieve. If not set, then all metrics will be returned. |
| transform | (Optional) a list describing a transformer for the given metric, if any. e.g. transform=list(op=foo_fn, name="foo") will rename the given metric to "foo" and apply function foo_fn to the metric values. |
Returns either a single value, or a list of values.
Many of these functions have an optional thresholds parameter. Currently only increments of 0.1 are allowed. If not specified, the functions will return all possible values. Otherwise, the function will return the value for the indicated threshold.
Currently, the these functions are only supported by H2OBinomialMetrics objects.
h2o.auc for AUC, h2o.giniCoef for the
GINI coefficient, and h2o.mse for MSE. See
h2o.performance for creating H2OModelMetrics objects.
if (FALSE) { library(h2o) h2o.init() prostate_path <- system.file("extdata", "prostate.csv", package = "h2o") prostate <- h2o.uploadFile(prostate_path) prostate$CAPSULE <- as.factor(prostate$CAPSULE) model <- h2o.gbm(x = 3:9, y = 2, training_frame = prostate, distribution = "bernoulli") perf <- h2o.performance(model, prostate) h2o.F1(perf) }