h2o (version 3.30.0.1)

h2o.metric: H2O Model Metric Accessor Functions

Description

A series of functions that retrieve model metric details.

Usage

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)

Arguments

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.

Value

Returns either a single value, or a list of values.

Details

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.

See Also

h2o.auc for AUC, h2o.giniCoef for the GINI coefficient, and h2o.mse for MSE. See h2o.performance for creating H2OModelMetrics objects.

Examples

# NOT RUN {
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)
# }

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