homogeneity_completeness_vmeasure: Homogeneity, completeness and V-Measure metrics for partition...
In agapow/subtypr: Robust and Validated Patient Subtyping for Precision Medicine
Description
Usage
Arguments
Details
Value
Examples
Description
External metrics.
Usage
1
homogeneity_completeness_vmeasure(pred_partition, true_partition)
Arguments
pred_partition
partition predicted by a method
true_partition
"true" partition, aka ground truth
Details
Like scikitlearn, we'll assume the inputs are two vectors of categoricals,
or things that can be turned into categoricals.
Value
The homogeneity, the completeness and the v_measure
of the two partitions.
Examples
1
2
3
x <- c(0, 0, 1, 1, 2, 2, 3, 3, 4, 4)
y <- c(1, 1, 2, 2, 2, 2, 6, 7, 9, 9)
homogeneity_completeness_vmeasure(x, y)
agapow/subtypr documentation built on May 5, 2019, 1:33 a.m.
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Description Usage Arguments Details Value Examples
Description
External metrics.
Usage
1 | homogeneity_completeness_vmeasure(pred_partition, true_partition)
|
Arguments
pred_partition |
partition predicted by a method |
true_partition |
"true" partition, aka ground truth |
Details
Like scikitlearn, we'll assume the inputs are two vectors of categoricals, or things that can be turned into categoricals.
Value
The homogeneity, the completeness and the v_measure of the two partitions.
Examples
1 2 3 | x <- c(0, 0, 1, 1, 2, 2, 3, 3, 4, 4)
y <- c(1, 1, 2, 2, 2, 2, 6, 7, 9, 9)
homogeneity_completeness_vmeasure(x, y)
|
R Package Documentation
Browse R Packages
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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