classif_params: Classification Parameters

In mlr3measures: Performance Measures for 'mlr3'

Classification Parameters

Description

Classification Parameters

Arguments

truth	(factor()) True (observed) labels. Must have the same levels and length as response.
response	(factor()) Predicted response labels. Must have the same levels and length as truth.
prob	(matrix()) Matrix of predicted probabilities, each column is a vector of probabilities for a specific class label. Columns must be named with levels of truth.
sample_weights	(numeric()) Vector of non-negative and finite sample weights. Must have the same length as truth. The vector gets automatically normalized to sum to one. Defaults to equal sample weights.
na_value	(numeric(1)) Value that should be returned if the measure is not defined for the input (as described in the note). Default is NaN.
...	(any) Additional arguments. Currently ignored.

mlr3measures documentation built on Sept. 12, 2024, 7:20 a.m.