mergeMeltScoreEmpirical: mergeMeltScoreEmpirical
In predomics/predomicspkg: Interpretable Prediction in Omics Data
mergeMeltScoreEmpirical R Documentation
mergeMeltScoreEmpirical
Description
mergeMeltScoreEmpirical returns a data frames that contain the performance of each digest in the list with their sparsity.
Usage
mergeMeltScoreEmpirical(list.results.digest, k_catalogue, score = "fit_")
Arguments
list.results.digest:
a list of digest objects one for each learner used. For example, list(res.terda.digest, res.terga.digest, res.terbeam.digest)
k_catalogue:
the k_catalogue that will serve to build the result matrix
score:
which score is to be used for value (default: fit_)
Details
Merge a list of empirical scores form digest results
Value
a data.frame
predomics/predomicspkg documentation built on Dec. 11, 2024, 11:06 a.m.
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| mergeMeltScoreEmpirical | R Documentation |
mergeMeltScoreEmpirical
Description
mergeMeltScoreEmpirical returns a data frames that contain the performance of each digest in the list with their sparsity.
Usage
mergeMeltScoreEmpirical(list.results.digest, k_catalogue, score = "fit_")
Arguments
list.results.digest: |
a list of digest objects one for each learner used. For example, list(res.terda.digest, res.terga.digest, res.terbeam.digest) |
k_catalogue: |
the k_catalogue that will serve to build the result matrix |
score: |
which score is to be used for value (default: fit_) |
Details
Merge a list of empirical scores form digest results
Value
a data.frame
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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