MultilabelACC: Accuracy (multilabel)
In measures: Performance Measures for Statistical Learning
View source: R/measures_multilabel.R
Description
Averaged proportion of correctly predicted labels with respect to the total number of labels for each instance,
following the definition by Charte and Charte: https: / /journal.r-project.org / archive / 2015 - 2 / charte-charte.pdf.
Fractions where the denominator becomes 0 are replaced with 1 before computing the average across all instances.
Usage
1
MultilabelACC(truth, response)
Arguments
truth
matrix of true values
response
matrix of predicted values
n = 20
set.seed(122)
truth = matrix(sample(c(0,1), 60, replace = TRUE), 20, 3)
response = matrix(sample(c(0,1), 60, replace = TRUE), 20, 3)
MultilabelACC(truth, response)
measures documentation built on Jan. 19, 2021, 5:08 p.m.
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View source: R/measures_multilabel.R
Description
Averaged proportion of correctly predicted labels with respect to the total number of labels for each instance, following the definition by Charte and Charte: https: / /journal.r-project.org / archive / 2015 - 2 / charte-charte.pdf. Fractions where the denominator becomes 0 are replaced with 1 before computing the average across all instances.
Usage
1 | MultilabelACC(truth, response)
|
Arguments
truth |
matrix of true values |
response |
matrix of predicted values n = 20 set.seed(122) truth = matrix(sample(c(0,1), 60, replace = TRUE), 20, 3) response = matrix(sample(c(0,1), 60, replace = TRUE), 20, 3) MultilabelACC(truth, response) |
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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